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ORCIDJournal of Imaging Informatics in Medicine, Volume 37
Volume 37, Number 1, 2024
- Elizabeth A. Krupinski, Victoria Barnosky:
Evolution of the Journal of Digital Imaging into the Journal of Imaging Informatics in Medicine. 1-2 - J. Martijn Nobel
, Sander Puts, Jasenko Krdzalic, Karen M. L. Zegers, Marc B. I. Lobbes, Simon G. F. Robben, André L. A. J. Dekker:
Natural Language Processing Algorithm Used for Staging Pulmonary Oncology from Free-Text Radiological Reports: "Including PET-CT and Validation Towards Clinical Use". 3-12 - Liangliang Zhang, Ming Fan, Lihua Li:
Deconvolution-Based Pharmacokinetic Analysis to Improve the Prediction of Pathological Information of Breast Cancer. 13-24 - Wyanne Law, Admir Terzic, Joshua Chaim, Joseph P. Erinjeri, Hedvig Hricak, Hebert Alberto Vargas, Anton S. Becker:
Integrated Automatic Examination Assignment Reduces Radiologist Interruptions: A 2-Year Cohort Study of 232, 022 Examinations. 25-30 - João Santinha, Vasileios K. Katsaros, George Stranjalis, Evangelia Liouta, Christos Boskos, Celso Matos, Catarina Viegas, Nickolas Papanikolaou:
Development of End-to-End AI-Based MRI Image Analysis System for Predicting IDH Mutation Status of Patients with Gliomas: Multicentric Validation. 31-44 - Sami Azam, Sidratul Montaha, Mohaimenul Azam Khan Raiaan, A. K. M. Rakibul Haque Rafid, Saddam Hossain Mukta, Mirjam Jonkman:
An Automated Decision Support System to Analyze Malignancy Patterns of Breast Masses Employing Medically Relevant Features of Ultrasound Images. 45-59 - Zhongsheng Zou, Changfei Gong, Lingpeng Zeng, Yu Guan, Bin Huang, Xiuwen Yu, Qiegen Liu, Minghui Zhang:
Invertible and Variable Augmented Network for Pretreatment Patient-Specific Quality Assurance Dose Prediction. 60-71 - Megan Courtman, Daniel H. Kim, Huub K. Wit, Hongrui Wang, Lingfen Sun, Emmanuel C. Ifeachor, Stephen Mullin, Mark Thurston:
Deep Learning Detection of Aneurysm Clips for Magnetic Resonance Imaging Safety. 72-80 - Huan Meng, Yu-Feng Sun, Yu Zhang, Ya-Nan Yu, Jing Wang, Jia-Ning Wang, Lin-Yan Xue, Xiao-Ping Yin:
Predicting Risk Stratification in Early-Stage Endometrial Carcinoma: Significance of Multiparametric MRI Radiomics Model. 81-91 - Akanksha Maurya, Ronald Joe Stanley, Norsang Lama, Anand K. Nambisan, Gehana Patel, Daniyal Saeed, Samantha Swinfard, Colin Smith, Sadhika Jagannathan, Jason R. Hagerty, William V. Stoecker:
Hybrid Topological Data Analysis and Deep Learning for Basal Cell Carcinoma Diagnosis. 92-106 - Mateo Gende, Lúa Castelo, Joaquim de Moura, Jorge Novo, Marcos Ortega:
Intra- and Inter-expert Validation of an Automatic Segmentation Method for Fluid Regions Associated with Central Serous Chorioretinopathy in OCT Images. 107-122 - Jingyu Zhong, Zhiyuan Wu, Lingyun Wang, Yong Chen, Yihan Xia, Lan Wang, Jianying Li, Wei Lu, Xiaomeng Shi, Jianxing Feng, Haipeng Dong, Huan Zhang, Weiwu Yao:
Impacts of Adaptive Statistical Iterative Reconstruction-V and Deep Learning Image Reconstruction Algorithms on Robustness of CT Radiomics Features: Opportunity for Minimizing Radiomics Variability Among Scans of Different Dose Levels. 123-133 - Donald R. Cantrell, Leon Cho, Chaochao Zhou, Syed Hasib Akhter Faruqui, Matthew B. Potts, Babak S. Jahromi, Ramez N. Abdalla, Ali Shaibani, Sameer A. Ansari:
Background Subtraction Angiography with Deep Learning Using Multi-frame Spatiotemporal Angiographic Input. 134-144 - Matheus Sampaio-Oliveira, Luiz Eduardo Marinho-Vieira, Matheus Barros-Costa, Matheus L. Oliveira:
Can Digital Enhancement Restore the Image Quality of Phosphor Plate-Based Radiographs Partially Damaged by Ambient Light? 145-150 - R. M. R. Shamija Sherryl, Thirassama Jaya:
Multi-Scale and Spatial Information Extraction for Kidney Tumor Segmentation: A Contextual Deformable Attention and Edge-Enhanced U-Net. 151-166 - Tetsuya Kobayashi, Yui Shigeki, Yoshiyuki Yamakawa, Yumi Tsutsumida, Tetsuro Mizuta, Kohei Hanaoka, Shota Watanabe, Daisuke Morimoto-ishikawa, Takahiro Yamada, Hayato Kaida, Kazunari Ishii:
Generating PET Attenuation Maps via Sim2Real Deep Learning-Based Tissue Composition Estimation Combined with MLACF. 167-179 - Jia Chen, Lei Liu, Ziying He, Danke Su, Chanzhen Liu:
CT-Based Radiomics and Machine Learning for Differentiating Benign, Borderline, and Early-Stage Malignant Ovarian Tumors. 180-195 - Ling Ma, Gen Li, Xingyu Feng, Qiliang Fan, Lizhi Liu:
TiCNet: Transformer in Convolutional Neural Network for Pulmonary Nodule Detection on CT Images. 196-208 - Yuling Lai, Yiyang Wu, Xiangyuan Chen, Wenchao Gu, Guoxia Zhou, Meilin Weng:
MRI-based Machine Learning Radiomics Can Predict CSF1R Expression Level and Prognosis in High-grade Gliomas. 209-229 - Haowen Yan, Gaoting Huang, Zhihe Yang, Yirong Chen, Zhiming Xiang:
Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics Model for Preoperative Predicting the Deep Stromal Invasion in Patients with Early Cervical Cancer. 230-246 - Gaurav Dubey, Somya Srivastava, Anant Kumar Jayswal, Mala Saraswat, Pooja Singh, Minakshi Memoria:
Fetal Ultrasound Segmentation and Measurements Using Appearance and Shape Prior Based Density Regression with Deep CNN and Robust Ellipse Fitting. 247-267 - Haishuang Sun, Min Liu, Anqi Liu, Mei Deng, Xiaoyan Yang, Han Kang, Ling Zhao, Yanhong Ren, Bingbing Xie, Rongguo Zhang, Huaping Dai:
Developing the Lung Graph-Based Machine Learning Model for Identification of Fibrotic Interstitial Lung Diseases. 268-279 - Abinaya K., Sivakumar B.:
A Deep Learning-Based Approach for Cervical Cancer Classification Using 3D CNN and Vision Transformer. 280-296 - Marcello Chang, Joshua Jay Reicher, Angad Kalra, Michael Muelly, Yousef Ahmad:
Analysis of Validation Performance of a Machine Learning Classifier in Interstitial Lung Disease Cases Without Definite or Probable Usual Interstitial Pneumonia Pattern on CT Using Clinical and Pathology-Supported Diagnostic Labels. 297-307 - Sheikh Burhan Ul Haque, Aasim Zafar:
Robust Medical Diagnosis: A Novel Two-Phase Deep Learning Framework for Adversarial Proof Disease Detection in Radiology Images. 308-338 - Michael K. Hoy, Vishal Desai, Simukayi Mutasa, Robert C. Hoy, Richard J. T. Gorniak, Jeffrey A. Belair:
Deep Learning-Assisted Identification of Femoroacetabular Impingement (FAI) on Routine Pelvic Radiographs. 339-346 - Herng-Hua Chang, Cheng-Zhe Wu, Audrey Haihong Gallogly:
Pulmonary Nodule Classification Using a Multiview Residual Selective Kernel Network. 347-362 - Chih-Hung Wang, Jia-Da Li, Cheng-Yi Wu, Yu-Chen Wu, Joyce Tay, Meng-Che Wu, Ching-Hang Hsu, Yi-Kuan Liu, Chu-Song Chen, Chien-Hua Huang:
Application of Machine Learning to Ultrasonography in Identifying Anatomical Landmarks for Cricothyroidotomy Among Female Adults: A Multi-center Prospective Observational Study. 363-373 - Yumeng Cui, Huali Wang, Rui Cao, Hong Bai, Dan Sun, Jiuxiang Feng, Xuefeng Lu:
The Segmentation of Multiple Types of Uterine Lesions in Magnetic Resonance Images Using a Sequential Deep Learning Method with Image-Level Annotations. 374-385 - Zaiba Amla, Parminder Singh Khehra, Ashley Mathialagan, Elodie Lugez:
Review of the Free Research Software for Computer-Assisted Interventions. 386-401 - Carl Sabottke, Jason Lee, Alan Chiang, Bradley Spieler, Mushtaq Raza:
Text Report Analysis to Identify Opportunities for Optimizing Target Selection for Chest Radiograph Artificial Intelligence Models. 402-411 - Venkata Sainath Gupta Thadikemalla, Niels K. Focke, Sudhakar Tummala:
A 3D Sparse Autoencoder for Fully Automated Quality Control of Affine Registrations in Big Data Brain MRI Studies. 412-427
Volume 37, Number 2, 2024
- Christopher J. Roth, Cheryl A. Petersilge, David A. Clunie, Alexander J. Towbin, Dawn Cram, Rik Primo, Xin Li, Seth J. Berkowitz, Victoria Barnosky, Elizabeth A. Krupinski:
HIMSS-SIIM Enterprise Imaging Community White Papers: Reflections and Future Directions. 429-443 - Zhaoyu Xing, Zuhui Zhu, Zhenxing Jiang, Jingshi Zhao, Qin Chen, Wei Xing, Liang Pan, Yan Zeng, Aie Liu, Jiule Ding:
Automatic Urinary Stone Detection System for Abdominal Non-Enhanced CT Images Reduces the Burden on Radiologists. 444-454 - Maryam Ashoori, Reza A. Zoroofi, Mohammad Sadeghi:
An Automatic Framework for Nasal Esthetic Assessment by ResNet Convolutional Neural Network. 455-470 - Xin Tie, Muheon Shin, Ali Pirasteh, Nevein Ibrahim, Zachary Huemann, Sharon M. Castellino, Kara M. Kelly, John W. Garrett, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw:
Personalized Impression Generation for PET Reports Using Large Language Models. 471-488 - Tarmo Äijö, Daniel Elgort, Murray Becker, Richard Herzog, Richard K. J. Brown, Benjamin L. Odry, Ron Vianu:
Improving the Reliability of Peer Review Without a Gold Standard. 489-503 - Jason Wang, Julia E. Goldberg, Tobias Block, Dana Ostrow, Dan Carbone, Michael Recht, Ankur M. Doshi:
Patterns of Access to Radiology Reports and Images Through a Patient Portal. 504-509 - Chongfeng Duan, Dapeng Hao, Jiufa Cui, Gang Wang, Wenjian Xu, Nan Li, Xuejun Liu:
An MRI-Based Deep Transfer Learning Radiomics Nomogram to Predict Ki-67 Proliferation Index of Meningioma. 510-519 - Yun Wang, Deng Lyu, Lei Hu, Junhong Wu, Shaofeng Duan, Taohu Zhou, Wenting Tu, Yi Xiao, Li Fan, Shiyuan Liu:
CT-Based Intratumoral and Peritumoral Radiomics Nomograms for the Preoperative Prediction of Spread Through Air Spaces in Clinical Stage IA Non-small Cell Lung Cancer. 520-535 - Osvaldo Matías Velarde, Clarissa Lin, Sarah Eskreis-Winkler, Lucas C. Parra:
Robustness of Deep Networks for Mammography: Replication Across Public Datasets. 536-546 - Chao Gao, Yongtao Shi, Shuai Yang, Bangjun Lei:
SAA-SDM: Neural Networks Faster Learned to Segment Organ Images. 547-562 - Jinwon Kim, Hyebin Lee, Sung Suk Oh, Jinhee Jang, Hyunyeol Lee:
Automated Quantification of Total Cerebral Blood Flow from Phase-Contrast MRI and Deep Learning. 563-574 - Ying Sun, Yuening Wang, Kexin Gan, Yuxin Wang, Ying Chen, Yun Ge, Jie Yuan, Hanzi Xu:
Reliable Delineation of Clinical Target Volumes for Cervical Cancer Radiotherapy on CT/MR Dual-Modality Images. 575-588 - Chih-Hung Wang, Weishan Chang, Meng-Rui Lee, Joyce Tay, Cheng-Yi Wu, Meng-Che Wu, Holger R. Roth, Dong Yang, Can Zhao, Weichung Wang, Chien-Hua Huang:
Deep Learning-based Diagnosis of Pulmonary Tuberculosis on Chest X-ray in the Emergency Department: A Retrospective Study. 589-600 - Jason Adleberg, C. L. Benitez, N. Primiano, A. Patel, D. Mogel, R. Kalra, A. Adhia, M. Berns, C. Chin, S. Tanghe, P. Yi, J. Zech, A. Kohli, Teresa Martin-Carreras, I. Corcuera-Solano, M. Huang, J. Ngeow:
Fully Automated Measurement of the Insall-Salvati Ratio with Artificial Intelligence. 601-610 - Xinhua Dai, Anjie Liu, Junhong Liu, Mengjun Zhan, Yuanyuan Liu, Wenchi Ke, Lei Shi, Xinyu Huang, Hu Chen, Zhenhua Deng, Fei Fan:
Machine Learning Supported the Modified Gustafson's Criteria for Dental Age Estimation in Southwest China. 611-619 - Amandine Crombé, Jean-Christophe Lecomte, Mylène Seux, Nathan Banaste, Guillaume Gorincour:
Using the Textual Content of Radiological Reports to Detect Emerging Diseases: A Proof-of-Concept Study of COVID-19. 620-632 - Hamid Alavi, Mehdi Seifi, Mahboubeh Rouhollahei, Mehravar Rafati, Masoud Arabfard:
Development of Local Software for Automatic Measurement of Geometric Parameters in the Proximal Femur Using a Combination of a Deep Learning Approach and an Active Shape Model on X-ray Images. 633-652 - Fei Zheng, Ping Yin, Li Yang, Yujian Wang, Wenhan Hao, Qi Hao, Xuzhu Chen, Nan Hong:
MRI-Based Machine Learning Fusion Models to Distinguish Encephalitis and Gliomas. 653-665 - Yifeng Yang, Ying Hu, Yang Chen, Weidong Gu, Shengdong Nie:
Identifying Leukoaraiosis with Mild Cognitive Impairment by Fusing Multiple MRI Morphological Metrics and Ensemble Machine Learning. 666-678 - Yi-Hui Lin, Chieh-Ting Lin, Ya-Han Chang, Yen-Yu Lin, Jen-Jee Chen, Chun-Rong Huang, Yu-Wei Hsu, Weir-Chiang You:
Development and Validation of a 3D Resnet Model for Prediction of Lymph Node Metastasis in Head and Neck Cancer Patients. 679-687 - Jiaoju Wang, Jiewen Luo, Jiehui Liang, Yangbo Cao, Jing Feng, Lingjie Tan, Zhengcheng Wang, Jingming Li, Alphonse Houssou Hounye, Muzhou Hou, Jinshen He:
Lightweight Attentive Graph Neural Network with Conditional Random Field for Diagnosis of Anterior Cruciate Ligament Tear. 688-705 - Krista Wernér, Turkka Anttila, Sina Hulkkonen, Timo Viljakka, Ville Haapamäki, Jorma O. Ryhänen:
Detecting Avascular Necrosis of the Lunate from Radiographs Using a Deep-Learning Model. 706-714 - Chao Zhu, Chang Rong, Jian Song, Xiaomin Zheng, Qi Wu, Jing Hu, Jianying Li, Xingwang Wu:
Evaluation of Mucosal Healing in Crohn's Disease: Radiomics Models of Intestinal Wall and Mesenteric Fat Based on Dual-Energy CT. 715-724 - Le Nguyen Binh, Nguyen Thanh Nhu, Vu Pham Thao Vy, Do Le Hoang Son, Truong Nguyen Khanh Hung, Nguyen Bach, Hoang Quoc Huy, Le Van Tuan, Nguyen Quoc Khanh Le, Jiunn-Horng Kang:
Multi-Class Deep Learning Model for Detecting Pediatric Distal Forearm Fractures Based on the AO/OTA Classification. 725-733 - Yoonho Nam, Su-Youn Kim, Kyu-Ah Kim, Euna Kwon, Yoo Hyun Lee, Jinhee Jang, Min Kyoung Lee, Jiwoong Kim, Yangsean Choi:
Development and Validation of Deep Learning-Based Automated Detection of Cervical Lymphadenopathy in Patients with Lymphoma for Treatment Response Assessment: A Bi-institutional Feasibility Study. 734-743 - Jing Chen, Xiaoyou Fan, Zhen Chen, Yichao Peng, Lichong Liang, Chengyue Su, Yun Chen, Jinghui Yao:
Enhancing YOLO5 for the Assessment of Irregular Pelvic Radiographs with Multimodal Information. 744-755 - Phuong T. Duong, Laura Santos, Hao-Yun Hsu, Sachin Jambawalikar, Simukayi Mutasa, Michael K. Nguyen, Andressa Guariento, Diego Jaramillo:
Deep Learning-Assisted Diffusion Tensor Imaging for Evaluation of the Physis and Metaphysis. 756-765 - Mohammadreza Salehi, Soheil Mohammadi, Hamid Harandi, Seyed Sina Zakavi, Ali Jahanshahi, Mohammad Shahrabi Farahani, Jim S. Wu:
Diagnostic Performance of Artificial Intelligence in Detection of Primary Malignant Bone Tumors: a Meta-Analysis. 766-777 - Serkan Savas:
Enhancing Disease Classification with Deep Learning: a Two-Stage Optimization Approach for Monkeypox and Similar Skin Lesion Diseases. 778-800 - Cemil Zalluhoglu, Dogan Akdogan, Derya Karakaya, Mehmet Serdar Güzel, M. Mahir Ülgü, Kemal Ardali, Atila Oguz Boyali, Ebru Akçapinar Sezer:
Region-Based Semi-Two-Stream Convolutional Neural Networks for Pressure Ulcer Recognition. 801-813 - E. Anbalagan, S. Malathi:
Horse Herd Optimization with Gate Recurrent Unit for an Automatic Classification of Different Facial Skin Disease. 814-830 - Xiang Li, Xuan Ma, Yibai Zhao, Jingjing Hu, Jie Liu, Zhicheng Yang, Fangkai Han, Jie Zhang, Weifan Liu, Zhongwei Zhou:
A Multi-center Dental Panoramic Radiography Image Dataset for Impacted Teeth, Periodontitis, and Dental Caries: Benchmarking Segmentation and Classification Tasks. 831-841 - Florent L. Besson, Sylvain Faure:
PET KinetiX - A Software Solution for PET Parametric Imaging at the Whole Field of View Level. 842-850 - Evgin Göçeri:
Polyp Segmentation Using a Hybrid Vision Transformer and a Hybrid Loss Function. 851-863 - Brandon J. Nelson, Daniel Gomez-Cardona, Jamison E. Thorne, Nathan R. Huber, Lifeng Yu, Shuai Leng, Cynthia H. McCollough, Andrew D. Missert:
Multiple Kernel Synthesis of Head CT Using a Task-Based Loss Function. 864-872 - Mladen Zecevic, Kyle Hasenstab, Kang Wang, Manish Dhyani, Guilherme M. Cunha:
Signal Intensity Trajectories Clustering for Liver Vasculature Segmentation and Labeling (LiVaS) on Contrast-Enhanced MR Images: A Feasibility Pilot Study. 873-883 - Ariel F. Pascaner, Antonio Rosato, Alice Fantazzini, Elena Vincenzi, Curzio Basso, Francesco Secchi, Mauro Lo Rito, Michele Conti:
Automatic 3D Segmentation and Identification of Anomalous Aortic Origin of the Coronary Arteries Combining Multi-view 2D Convolutional Neural Networks. 884-891 - Daniel Berthe, Anna Kolb, Abdulrahman Rabi, Thorsten Sellerer, Villseveri Somerkivi, Georg Constantin Feuerriegel, Andreas Philipp Sauter, Felix Meurer, York Hämisch, Tuomas Pantsar, Henrik Lohman, Daniela Pfeiffer, Franz Pfeiffer:
Evaluation of Spectral X-Ray Imaging for Panoramic Dental Images Based on a Simulation Framework. 892-898 - Woo Yeon Park, Kyulee Jeon, Teri Sippel Schmidt, Haridimos Kondylakis, Tarik K. Alkasab, Blake E. Dewey, Seng Chan You, Paul G. Nagy:
Development of Medical Imaging Data Standardization for Imaging-Based Observational Research: OMOP Common Data Model Extension. 899-908 - Ameena Elahi, Nikki Fennell, Liana Watson:
Certified Imaging Informatics Professionals (CIIP) Demonstrate Value to the Healthcare Industry and Focus on Quality Through the ABII 10-Year Requirements Practice Option. 909-914
Volume 37, Number 3, 2024
- Guodong Zhang, Wenwen Gu, Suran Wang, Yanlin Li, Dazhe Zhao, Tingyu Liang, Zhaoxuan Gong, Ronghui Ju:
MOTC: Abdominal Multi-objective Segmentation Model with Parallel Fusion of Global and Local Information. 1-16 - Jinmin Kim, Deokgi Jeung, Ranyeong Cho, Byoungeun Yang, Jaesung Hong:
A Proof of Concept: Optimized Jawbone-Reduction Model for Mandibular Fracture Surgery. 1151-1159 - Sadia Sultana Chowa, Sami Azam, Sidratul Montaha, Md. Rahad Islam Bhuiyan, Mirjam Jonkman:
Improving the Automated Diagnosis of Breast Cancer with Mesh Reconstruction of Ultrasound Images Incorporating 3D Mesh Features and a Graph Attention Network. 1067-1085 - Yuan Chai:
Letter to the Editor Regarding the Article "Comparison of Transfer Learning Models in Pelvic Tilt and Rotation Measurement in Pediatric Anteroposterior Pelvic Radiographs". 1259-1260 - Anton S. Becker, Joshua Chaim, Hebert Alberto Vargas:
Streamlining Radiology Workflows Through the Development and Deployment of Automated Microservices. 945-951 - Salvatore Gitto, Renato Cuocolo, Vincenzo Giannetta, Julietta Badalyan, Filippo Di Luca, Stefano Fusco, Giulia Zantonelli, Domenico Albano, Carmelo Messina, Luca Maria Sconfienza:
Effects of Interobserver Segmentation Variability and Intensity Discretization on MRI-Based Radiomic Feature Reproducibility of Lipoma and Atypical Lipomatous Tumor. 1187-1200 - B. Christina Sweetline, C. Vijayakumaran, A. Samydurai:
Overcoming the Challenge of Accurate Segmentation of Lung Nodules: A Multi-crop CNN Approach. 988-1007 - Francesco Prinzi, Alessia Orlando, Salvatore Gaglio, Salvatore Vitabile:
Interpretable Radiomic Signature for Breast Microcalcification Detection and Classification. 1038-1053 - Tomohiro Kikuchi, Shouhei Hanaoka, Takahiro Nakao, Tomomi Takenaga, Yukihiro Nomura, Harushi Mori, Takeharu Yoshikawa:
Synthesis of Hybrid Data Consisting of Chest Radiographs and Tabular Clinical Records Using Dual Generative Models for COVID-19 Positive Cases. 1217-1227 - Yu Wang, Zheng Sun, Zhi Liu, Jie Lu, Nan Zhang:
A Motion-Aware DNN Model with Edge Focus Loss and Quality Control for Short-Axis Left Ventricle Segmentation of Cine MR Sequences. 1-13 - MM Zoghby, Bradley J. Erickson, Gian Marco Conte:
Generative Adversarial Networks for Brain MRI Synthesis: Impact of Training Set Size on Clinical Application. 1228-1238 - Alexander J. Towbin, Delaney D. Ding, Moneif Eid, Heather Kimball, Julia Komissarchik, John Memarian, Seetharam C. Chadalavada:
Special Challenges of Sensitive Images: A HIMSS-SIIM Enterprise Imaging Community Whitepaper. 915-921 - Akanksha Maurya, Ronald Joe Stanley, Hemanth Y. Aradhyula, Norsang Lama, Anand K. Nambisan, Gehana Patel, Daniyal Saeed, Samantha Swinfard, Colin Smith, Sadhika Jagannathan, Jason R. Hagerty, William V. Stoecker:
Basal Cell Carcinoma Diagnosis with Fusion of Deep Learning and Telangiectasia Features. 1137-1150 - Yuting Li, Ruize Yu, Huan Chang, Wanying Yan, Dawei Wang, Fuyan Li, Yi Cui, Yong Wang, Xiao Wang, Qingqing Yan, Xinhui Liu, Wenjing Jia, Qingshi Zeng:
Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study. 976-987 - Yiman Liu, Qiming Huang, Xiaoxiang Han, Tongtong Liang, Zhifang Zhang, Xiuli Lu, Bin Dong, Jiajun Yuan, Yan Wang, Menghan Hu, Jinfeng Wang, Angelos Stefanidis, Jionglong Su, Jiangang Chen, Qingli Li, Yuqi Zhang:
Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning. 965-975 - Yuwen Zeng, Xiaoyong Zhang, Jiaoyang Wang, Akihito Usui, Kei Ichiji, Ivo Bukovsky, Shuo-Yan Chou, Masato Funayama, Noriyasu Homma:
Inconsistency between Human Observation and Deep Learning Models: Assessing Validity of Postmortem Computed Tomography Diagnosis of Drowning. 1-10 - Xudong Zhang, Yaru Gao, Yunge Zhang, Fengling Li, Huanjie Li, Fengchun Lei:
Identification of Autism Spectrum Disorder Using Topological Data Analysis. 1023-1037 - Abdullahi Umar Ibrahim, Fikret Dirilenoglu, Uguray Payam Hacisalihoglu, Ahmet Ilhan, Omid Mirzaei:
Classification of H. pylori Infection from Histopathological Images Using Deep Learning. 1177-1186 - R. Janani Abinaya, G. Rajakumar:
Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization. 1008-1022 - Ali Ganjizadeh, Stephanie Zawada, Steve G. Langer, Bradley J. Erickson:
Visualizing Clinical Data Retrieval and Curation in Multimodal Healthcare AI Research: A Technical Note on RIL-workflow. 1239-1247 - Nan Xu, Jiajun Wang, Gang Dai, Tao Lu, Shu Li, Kexue Deng, Jiangdian Song:
EfficientNet-Based System for Detecting EGFR-Mutant Status and Predicting Prognosis of Tyrosine Kinase Inhibitors in Patients with NSCLC. 1086-1099 - Chi-Tung Cheng, Hou-Hsien Lin, Chih-Po Hsu, Huan-Wu Chen, Jen-Fu Huang, Chi-Hsun Hsieh, Chih-Yuan Fu, I-Fang Chung, Chien-Hung Liao:
Deep Learning for Automated Detection and Localization of Traumatic Abdominal Solid Organ Injuries on CT Scans. 1113-1123 - Yuan Gui, Fen Chen, Jialiang Ren, Limei Wang, Kuntao Chen, Jing Zhang:
MRI- and DWI-Based Radiomics Features for Preoperatively Predicting Meningioma Sinus Invasion. 1054-1066 - Chan-Hyuk Lee, Sang Hyuk Lee, Hyo-Sung Kwak, Yeong-Gon Kwak, Robert S. Rosenson, Young I. Cho, Seul-Ki Jeong:
Validation of Signal Intensity Gradient from TOF-MRA for Wall Shear Stress by Phase-Contrast MR. 1248-1258 - Lili Guo, Changsheng Zhou, Jingxu Xu, Chencui Huang, Yizhou Yu, Guangming Lu:
Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance. 922-934 - Yasuyuki Ueda, Daiki Ogawa, Takayuki Ishida:
Patient Re-Identification Based on Deep Metric Learning in Trunk Computed Tomography Images Acquired from Devices from Different Vendors. 1124-1136 - Taiyu Yang, Danyan Liu, Zexu Zhang, Ri Sa, Feng Guan:
Predicting T-Cell Lymphoma in Children From 18F-FDG PET-CT Imaging With Multiple Machine Learning Models. 952-964 - Zijun Wang, Kaitai Han, Wu Liu, Zhenghui Wang, Chaojing Shi, Xi Liu, Mengyuan Huang, Guocheng Sun, Shitou Liu, Qianjin Guo:
Fast Real-Time Brain Tumor Detection Based on Stimulated Raman Histology and Self-Supervised Deep Learning Model. 1160-1176
Volume 37, Number 4, 2024
- Langtao Zhou, Huiting Wu, Hong Zhou:
Correlation Between Cognitive Impairment and Lenticulostriate Arteries: A Clinical and Radiomics Analysis. 1261-1272 - Elisavet Kapetanou, Stylianos Malamas, Dimitrios Leventis, Apostolos Karantanas, Michail E. Klontzas:
Developing a Radiomics Atlas Dataset of normal Abdominal and Pelvic computed Tomography (RADAPT). 1273-1281 - Bing Quan, Jinghuan Li, Hailin Mi, Miao Li, Wenfeng Liu, Fan Yao, Rongxin Chen, Yan Shan, Pengju Xu, Zhenggang Ren, Xin Yin:
Development and Preliminary Validation of a Novel Convolutional Neural Network Model for Predicting Treatment Response in Patients with Unresectable Hepatocellular Carcinoma Receiving Hepatic Arterial Infusion Chemotherapy. 1282-1296 - Mohammad Amin Salehi, Hamid Harandi, Soheil Mohammadi, Mohammad Shahrabi Farahani, Shayan Shojaei, Ramy R. Saleh:
Diagnostic Performance of Artificial Intelligence in Detection of Hepatocellular Carcinoma: A Meta-analysis. 1297-1311 - Jiaxi Lin, Jin Yang, Minyue Yin, Yuxiu Tang, Liquan Chen, Chang Xu, Shiqi Zhu, Jingwen Gao, Lu Liu, Xiaolin Liu, Chenqi Gu, Zhou Huang, Yao Wei, Jinzhou Zhu:
Development and Validation of Multimodal Models to Predict the 30-Day Mortality of ICU Patients Based on Clinical Parameters and Chest X-Rays. 1312-1322 - Yi Wang, Juan Ye, Kai Zhou, Nian Chen, Gang Huang, Guangyong Feng, Guihai Zhang, Xiaoxia Gou:
Radiomics Features on Enhanced Computed Tomography Predict FOXP3 Expression and Clinical Prognosis in Patients with Head and Neck Squamous Cell Carcinoma. 1323-1335 - Xueyao Lin, Chaochao Wang, Jingjing Zheng, Mengru Liu, Ming Li, Hongbin Xu, Haibo Dong:
Image Omics Nomogram Based on Incoherent Motion Diffusion-Weighted Imaging in Voxels Predicts ATRX Gene Mutation Status of Brain Glioma Patients. 1336-1345 - Dina Ahmed Ragab, Salema Fayed, Noha Ghatwary:
DeepCSFusion: Deep Compressive Sensing Fusion for Efficient COVID-19 Classification. 1346-1358 - Chenggang Jiang, Chen Sun, Xi Wang, Shunchang Ma, Wang Jia, Dainan Zhang:
BTK Expression Level Prediction and the High-Grade Glioma Prognosis Using Radiomic Machine Learning Models. 1359-1374 - Kyungjin Cho, Ki Duk Kim, Jiheon Jeong, Yujin Nam, Jeeyoung Kim, Changyong Choi, Soyoung Lee, Gil-Sun Hong, Joon Beom Seo, Namkug Kim:
Approximating Intermediate Feature Maps of Self-Supervised Convolution Neural Network to Learn Hard Positive Representations in Chest Radiography. 1375-1385 - Ronghui Tian, Guoxiu Lu, Nannan Zhao, Wei Qian, He Ma, Wei Yang:
Constructing the Optimal Classification Model for Benign and Malignant Breast Tumors Based on Multifeature Analysis from Multimodal Images. 1386-1400 - Qi Wan, Jisoo Kim, Clifford Lindsay, Xin Chen, Jing Li, J. Bryan Iorgulescu, Raymond Y. Huang, Chenxi Zhang, David Reardon, Geoffrey S. Young, Lei Qin:
Auto-segmentation of Adult-Type Diffuse Gliomas: Comparison of Transfer Learning-Based Convolutional Neural Network Model vs. Radiologists. 1401-1410 - Paul M. Murphy:
Towards an EKG for SBO: A Neural Network for Detection and Characterization of Bowel Obstruction on CT. 1411-1423 - Weidong Wang, Hongme Zhang, Yizhen Li, Yi Wang, Qingfeng Zhang, Geqi Ding, Lixue Yin, Jinshan Tang, Bo Peng:
An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks. 1424-1439 - Barsha Abhisheka, Saroj Kr. Biswas, Biswajit Purkayastha:
HBMD-Net: Feature Fusion Based Breast Cancer Classification with Class Imbalance Resolution. 1440-1457 - Miguel Molina-Moreno, Iván González-Díaz, Maite Rivera Gorrín, Víctor Burguera Vion, Fernando Díaz-de-María:
URI-CADS: A Fully Automated Computer-Aided Diagnosis System for Ultrasound Renal Imaging. 1458-1474 - Kepei Xu, Meiqi Hua, Ting Mai, Xiaojing Ren, Xiaozheng Fang, Chunjie Wang, Min Ge, Hua Qian, Maosheng Xu, Ruixin Zhang:
A Multiparametric MRI-based Radiomics Model for Stratifying Postoperative Recurrence in Luminal B Breast Cancer. 1475-1487 - Selvakanmani S, G. Dharani Devi, Rekha V, J. Jeyalakshmi:
Privacy-Preserving Breast Cancer Classification: A Federated Transfer Learning Approach. 1488-1504 - Fenglin Cai, Jiaying Wen, Fangzhou He, Yulong Xia, Weijun Xu, Yong Zhang, Li Jiang, Jie Li:
SC-Unext: A Lightweight Image Segmentation Model with Cellular Mechanism for Breast Ultrasound Tumor Diagnosis. 1505-1515 - Ming Cheng, Hanyue Zhang, Wenpeng Huang, Fei Li, Jianbo Gao:
Deep Learning Radiomics Analysis of CT Imaging for Differentiating Between Crohn's Disease and Intestinal Tuberculosis. 1516-1528 - Wenjian Yao, Jiajun Bai, Wei Liao, Yuheng Chen, Mengjuan Liu, Yao Xie:
From CNN to Transformer: A Review of Medical Image Segmentation Models. 1529-1547 - Hendrik J. H. Dreesen, C. Stroszczynski, M. M. Lell:
Optimizing Coronary Computed Tomography Angiography Using a Novel Deep Learning-Based Algorithm. 1548-1556 - Qing Chang, Yaqi Wang, Jieming Zhang:
Independently Trained Multi-Scale Registration Network Based on Image Pyramid. 1557-1566 - Akiyoshi Hizukuri, Ryohei Nakayama, Mariko Goto, Koji Sakai:
Computerized Segmentation Method for Nonmasses on Breast DCE-MRI Images Using ResUNet++ with Slice Sequence Learning and Cross-Phase Convolution. 1567-1578 - Jie Ying, Xin Jing, Feng Gao, Jiejun Cheng, Le Fu, Haima Yang:
Prediction of Ablation Rate for High-Intensity Focused Ultrasound Therapy of Adenomyosis in MR Images Based on Multi-model Fusion. 1579-1590 - Afnan M. Alhassan:
Identification and Localization of Indolent and Aggressive Prostate Cancers Using Multilevel Bi-LSTM. 1591-1608 - Koichiro Yasaka, Hiroyuki Saigusa, Osamu Abe:
Effects of Intravenous Infusion of Iodine Contrast Media on the Tracheal Diameter and Lung Volume Measured with Deep Learning-Based Algorithm. 1609-1617 - Kuniki Imagawa, Kohei Shiomoto:
Evaluation of Effectiveness of Self-Supervised Learning in Chest X-Ray Imaging to Reduce Annotated Images. 1618-1624 - Upasana Chutia, Anand Shanker Tewari, Jyoti Prakash Singh, Vikash Kumar Raj:
Classification of Lung Diseases Using an Attention-Based Modified DenseNet Model. 1625-1641 - Giulio Del Corso, Danila Germanese, Claudia Caudai, Giada Anastasi, Paolo Belli, Alessia Formica, Alberto Nicolucci, Simone Palma, Maria Antonietta Pascali, Stefania Pieroni, Charlotte Trombadori, Sara Colantonio, Michela Franchini, Sabrina Molinaro:
Adaptive Machine Learning Approach for Importance Evaluation of Multimodal Breast Cancer Radiomic Features. 1642-1651 - Zachary Huemann, Xin Tie, Junjie Hu, Tyler J. Bradshaw:
ConTEXTual Net: A Multimodal Vision-Language Model for Segmentation of Pneumothorax. 1652-1663 - Mana Moassefi, Yashbir Singh, Gian Marco Conte, Bardia Khosravi, Pouria Rouzrokh, Sanaz Vahdati, Nabile M. Safdar, Linda Moy, Felipe Kitamura, Amilcare Gentili, Paras Lakhani, Nina Kottler, Safwan S. Halabi, Joseph H. Yacoub, Yuankai Hou, Khaled Younis, Bradley J. Erickson, Elizabeth A. Krupinski, Shahriar Faghani:
Checklist for Reproducibility of Deep Learning in Medical Imaging. 1664-1673 - Jongwook Whangbo, Young Seop Lee, Young Jae Kim, Jisup Kim, Kwang Gi Kim:
Predicting Mismatch Repair Deficiency Status in Endometrial Cancer through Multi-Resolution Ensemble Learning in Digital Pathology. 1674-1682 - Jong Chan Yeom, Jae Hoon Kim, Young Jae Kim, Jisup Kim, Kwang Gi Kim:
A Comparative Study of Performance Between Federated Learning and Centralized Learning Using Pathological Image of Endometrial Cancer. 1683-1690 - Adriano Barbosa-Silva, Alessandro Santana Martins, Thaína Aparecida Azevedo Tosta, Adriano M. Loyola, Sérgio V. Cardoso, Leandro Alves Neves, Paulo Rogério de Faria, Marcelo Zanchetta do Nascimento:
OralEpitheliumDB: A Dataset for Oral Epithelial Dysplasia Image Segmentation and Classification. 1691-1710 - Monika Pytlarz, K. Wojnicki, P. Pilanc, B. Kaminska, Alessandro Crimi:
Deep Learning Glioma Grading with the Tumor Microenvironment Analysis Protocol for Comprehensive Learning, Discovering, and Quantifying Microenvironmental Features. 1711-1727 - Arshi Parvaiz, Esha Sadia Nasir, Muhammad Moazam Fraz:
From Pixels to Prognosis: A Survey on AI-Driven Cancer Patient Survival Prediction Using Digital Histology Images. 1728-1751 - Ekta, Vandana Bhatia:
Auto-BCS: A Hybrid System for Real-Time Breast Cancer Screening from Pathological Images. 1752-1766 - Rodrigo Escobar Díaz Guerrero, Lina Carvalho, Thomas Bocklitz, Jürgen Popp, José Luís Oliveira:
A Data Augmentation Methodology to Reduce the Class Imbalance in Histopathology Images. 1767-1782 - Prem Kumari Verma, Jagdeep Kaur:
Systematic Review of Retinal Blood Vessels Segmentation Based on AI-driven Technique. 1783-1799 - Shuxi Xu, Houli Peng, Lanxin Yang, Wenjie Zhong, Xiang Gao, Jinlin Song:
An Automatic Grading System for Orthodontically Induced External Root Resorption Based on Deep Convolutional Neural Network. 1800-1811 - Norsang Lama, Ronald Joe Stanley, Binita Lama, Akanksha Maurya, Anand K. Nambisan, Jason R. Hagerty, Thanh Phan, William Van Stoecker:
LAMA: Lesion-Aware Mixup Augmentation for Skin Lesion Segmentation. 1812-1823 - Luiz Guilherme Kasputis Zanini, Izabel Regina Fischer Rubira-Bullen, Fátima de Lourdes dos Santos Nunes:
A Systematic Review on Caries Detection, Classification, and Segmentation from X-Ray Images: Methods, Datasets, Evaluation, and Open Opportunities. 1824-1845 - Lucas Krenmayr, Reinhold von Schwerin, Daniel Schaudt, Pascal Riedel, Alexander Hafner:
DilatedToothSegNet: Tooth Segmentation Network on 3D Dental Meshes Through Increasing Receptive Vision. 1846-1862 - Jae Hyuk Shim, Woo Seok Kim, Kwang Gi Kim, Gi Taek Yee, Young Jae Kim, Tae Seok Jeong:
Automated Segmentation and Diagnostic Measurement for the Evaluation of Cervical Spine Injuries Using X-Rays. 1863-1873 - Bo Pang, Lianghong Chen, Qingchuan Tao, Enhui Wang, Yanmei Yu:
GA-UNet: A Lightweight Ghost and Attention U-Net for Medical Image Segmentation. 1874-1888 - Martin Bittner-Frank, Andreas Strassl, Ewald Unger, Lena Hirtler, Barbara Eckhart, Markus Koenigshofer, Alexander Stoegner, Arastoo Nia, Domenik Popp, Franz Kainberger, Reinhard Windhager, Francesco Moscato, Emir Benca:
Accuracy Analysis of 3D Bone Fracture Models: Effects of Computed Tomography (CT) Imaging and Image Segmentation. 1889-1901 - Jianning Chi, Xiaolin Wei, Zhiyi Sun, Yongming Yang, Bin Yang:
Low-Dose CT Image Super-resolution Network with Noise Inhibition Based on Feedback Feature Distillation Mechanism. 1902-1921 - Wuqi Li, Shitong Mao, Amanda S. Mahoney, James L. Coyle, Ervin Sejdic:
Automatic Tracking of Hyoid Bone Displacement and Rotation Relative to Cervical Vertebrae in Videofluoroscopic Swallow Studies Using Deep Learning. 1922-1932 - Kaixuan Yao, Wei Deng, Rong He, Hui Gao, Linlin Wang, Ren Zhao, Xiuzheng Yue, Yongqiang Yu, Liang Zhong, Xiaohu Li:
Comparing Strain Assessment in Compressed Sensing and Conventional Cine MRI. 1933-1943 - Jianning Chi, Zhiyi Sun, Shuyu Tian, Huan Wang, Siqi Wang:
A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising. 1944-1959 - Chenyu Jiang, Jingxin Zhang, Wenhuan Li, Yali Li, Ming Ni, Dan Jin, Yan Zhang, Liang Jiang, Huishu Yuan:
Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs - A Preliminary Study. 1960-1968 - Hang Cheng, Xuewen Hou, Gang Huang, Shouqiang Jia, Guang Yang, Shengdong Nie:
Feature Fusion for Multi-Coil Compressed MR Image Reconstruction. 1969-1979 - Olivier Taton, Alain Van Muylem, Dimitri Leduc, Pierre Alain Gevenois:
CT-Based Evaluation of the Shape of the Diaphragm Using 3D Slicer. 1980-1990 - Hülya Dogan, Ramazan Ozgur Dogan, Ilyas Ay, Sena F. Sezen:
DL-EDOF: Novel Multi-Focus Image Data Set and Deep Learning-Based Approach for More Accurate and Specimen-Free Extended Depth of Focus. 1991-2013
Volume 37, Number 5, 2024
- Luong Huu Dang, Shih-Han Hung, Nhi Thao Ngoc Le, Wei-Kai Chuang, Jeng-You Wu, Ting-Chieh Huang, Nguyen Quoc Khanh Le:
Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data. 2474-2489 - Qingbo Ji, Tingshuo Yin, Pengfei Zhang, Qingquan Liu, Changbo Hou:
Study on Fine-Grained Visual Classification of Low-Resolution Urinary Erythrocyte. 2513-2523 - Hyunsu Jeong, Hyunseok Lim, Chiho Yoon, Jongjun Won, Grace Yoojin Lee, Ezequiel de la Rosa, Jan S. Kirschke, Bumjoon Kim, Namkug Kim, Chulhong Kim:
Robust Ensemble of Two Different Multimodal Approaches to Segment 3D Ischemic Stroke Segmentation Using Brain Tumor Representation Among Multiple Center Datasets. 2375-2389 - Yu Wang, Haoxiang Ni, Jielu Zhou, Lihe Liu, Jiaxi Lin, Minyue Yin, Jingwen Gao, Shiqi Zhu, Qi Yin, Jinzhou Zhu, Rui Li:
A Semi-Supervised Learning Framework for Classifying Colorectal Neoplasia Based on the NICE Classification. 2342-2353 - Yuhei Koike, Shingo Ohira, Sayaka Kihara, Yusuke Anetai, Hideki Takegawa, Satoaki Nakamura, Masayoshi Miyazaki, Koji Konishi, Noboru Tanigawa:
Synthetic Low-Energy Monochromatic Image Generation in Single-Energy Computed Tomography System Using a Transformer-Based Deep Learning Model. 2688-2697 - Pragya Gupta, Nishant Jain:
Segmentation-Based Fusion of CT and MR Images. 2635-2648 - Uzma Saghir, Shailendra Kumar Singh, Moin Hasan:
Skin Cancer Image Segmentation Based on Midpoint Analysis Approach. 2581-2596 - Chandan Singh, Sukhjeet Kaur Ranade, Dalvinder Kaur, Anu Bala:
An Intuitionistic Fuzzy C-Means and Local Information-Based DCT Filtering for Fast Brain MRI Segmentation. 2287-2310 - Yassine Oukdach, Anass Garbaz, Zakaria Kerkaou, Mohamed El Ansari, Lahcen Koutti, Ahmed Fouad El Ouafdi, Mouna Salihoun:
UViT-Seg: An Efficient ViT and U-Net-Based Framework for Accurate Colorectal Polyp Segmentation in Colonoscopy and WCE Images. 2354-2374 - Tiphaine Diot-Dejonghe, Benjamin Leporq, Amine Bouhamama, Hélène Ratiney, Frank Pilleul, Olivier Beuf, Frederic Cervenansky:
Development of a Secure Web-Based Medical Imaging Analysis Platform: The AWESOMME Project. 2612-2626 - Mohammed Lubbad, Ikbal Leblebicioglu Kurtulus, Dervis Karaboga, Kerem Kilic, Alper Bastürk, Bahriye Akay, Özkan U. Nalbantoglu, Ozden Melis Durmaz Yilmaz, Mustafa Ayata, Serkan Yilmaz, Ishak Paçal:
A Comparative Analysis of Deep Learning-Based Approaches for Classifying Dental Implants Decision Support System. 2559-2580 - Chao Ma, Yuan Gu, Ziyang Wang:
TriConvUNeXt: A Pure CNN-Based Lightweight Symmetrical Network for Biomedical Image Segmentation. 2311-2323 - Francesca Lo Iacono, Riccardo Maragna, Gianluca Pontone, Valentina D. A. Corino:
A Novel Data Augmentation Method for Radiomics Analysis Using Image Perturbations. 2401-2414 - Priya Deshpande, Alexander Rasin:
Correlation Aware Relevance-Based Semantic Index for Clinical Big Data Repository. 2597-2611 - Ziping Chu, Sonit Singh, Arcot Sowmya:
Robust Automated Tumour Segmentation Network Using 3D Direction-Wise Convolution and Transformer. 2444-2453 - Wutong Chen, Du Junsheng, Yanzhen Chen, Yifeng Fan, Hengzhi Liu, Chang Tan, Xuanming Shao, Xinzhi Li:
The Classification of Lumbar Spondylolisthesis X-Ray Images Using Convolutional Neural Networks. 2264-2273 - Kuan-Chih Huang, Donna Shu-Han Lin, Geng-Shi Jeng, Ting-Tse Lin, Lian-Yu Lin, Chih-Kuo Lee, Lung-Chun Lin:
Left Ventricular Segmentation, Warping, and Myocardial Registration for Automated Strain Measurement. 2274-2286 - Lihong Xing, Shuping Wang, Li-Yong Zhuo, Yu Zhang, Jia-Ning Wang, Ze-Peng Ma, Ying-Jia Zhao, Shuang-Rui Yuan, Qian-He Zu, Xiao-Ping Yin:
Comparison of Machine Learning Models Using Diffusion-Weighted Images for Pathological Grade of Intrahepatic Mass-Forming Cholangiocarcinoma. 2252-2263 - Jacob A. Macdonald, Katelyn R. Morgan, Brandon Konkel, Kulsoom Abdullah, Mark Martin, Cory Ennis, Joseph Y. Lo, Marissa Stroo, Denise Snyder, Mustafa R. Bashir:
A Method for Efficient De-identification of DICOM Metadata and Burned-in Pixel Text. 1-7 - Daniel D. Kim, Rajat S. Chandra, Li Yang, Jing Wu, Xue Feng, Michael Atalay, Chetan Bettegowda, Craig K. Jones, Haris I. Sair, Wei-hua Liao, Chengzhang Zhu, Beiji Zou, Anahita Fathi Kazerooni, Ali Nabavizadeh, Zhicheng Jiao, Jian Peng, Harrison X. Bai:
Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction. 2099-2107 - Jun-Yan Yue, Pei-Cheng Li, Mei-Xia Li, Qing-Wu Wu, Chang-Hua Liang, Jie Chen, Zhi-Ping Zhu, Pei-Heng Li, Wen-Guang Dou, Jian-Bo Gao:
An Exploratory Pilot Study on the Application of Radiofrequency Ablation for Atrial Fibrillation Guided by Computed Tomography-Based 3D Printing Technology. 2025-2037 - Joren Brunekreef:
Letter to the Editor Regarding Article "Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset". 2706-2708 - Maide Cakir, Gökalp Tulum, Ferhat Cuce, Kerim Bora Yilmaz, Ayse Aralasmak, Muhammet Ikbal Isik, Hüseyin Canbolat:
Differential Diagnosis of Diabetic Foot Osteomyelitis and Charcot Neuropathic Osteoarthropathy with Deep Learning Methods. 2454-2465 - Enxiang Shen, Caozhe Li, Kanglian Zhao, Jie Yuan, Paul Carson:
Image Quality Enhancement for Digital Breast Tomosynthesis: High-Density Object Artifact Reduction. 2649-2661 - Muhammad Usman Saeed, Bin Wang, Jinfang Sheng, Hussain Mobarak Albarakati:
An Automated Multi-scale Feature Fusion Network for Spine Fracture Segmentation Using Computed Tomography Images. 2216-2226 - Sara El-Ateif, Ali Idri:
Multimodality Fusion Strategies in Eye Disease Diagnosis. 2524-2558 - Yang Li, Maliha R. Imami, Linmei Zhao, Alireza Amindarolzarbi, Esther Mena, Jeffrey Leal, Junyu Chen, Andrei Gafita, Andrew F. Voter, Xin Li, Yong Du, Chengzhang Zhu, Peter L. Choyke, Beiji Zou, Zhicheng Jiao, Steven P. Rowe, Martin G. Pomper, Harrison X. Bai:
An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer. 2206-2215 - Kesavan Venkatesh, Simukayi Mutasa, Fletcher Moore, Jeremias Sulam, Paul H. Yi:
Gradient-Based Saliency Maps Are Not Trustworthy Visual Explanations of Automated AI Musculoskeletal Diagnoses. 2490-2499 - Karthik Kantipudi, Jingwen Gu, Vy C. B. Bui, Hang Yu, Stefan Jäger, Ziv Yaniv:
Automated Pulmonary Tuberculosis Severity Assessment on Chest X-rays. 2173-2185 - He Ren, Qiubo Wang, Zhengguang Xiao, Runwei Mo, Jiachen Guo, Gareth Richard Hide, Mengting Tu, Yanan Zeng, Chen Ling, Ping Li:
Fusing Diverse Decision Rules in 3D-Radiomics for Assisting Diagnosis of Lung Adenocarcinoma. 2135-2148 - Getao Du, Peng Zhang, Jianzhong Guo, Xu Zhou, Guanghan Kan, Jiajie Jia, Xiaoping Chen, Jimin Liang, Yonghua Zhan:
Exploring Radiomics Features Based on H&E Images as Potential Biomarkers for Evaluating Muscle Atrophy: A Preliminary Study. 2324-2341 - Swati Rai, Jignesh S. Bhatt, Sarat Kumar Patra:
An AI-Based Low-Risk Lung Health Image Visualization Framework Using LR-ULDCT. 2047-2062 - Vishal Patel, Shengzhen Tao, Xiangzhi Zhou, Chen Lin, Erin M. Westerhold, Sanjeet Grewal, Erik H. Middlebrooks:
Real-Time Optimal Synthetic Inversion Recovery Image Selection (RT-OSIRIS) for Deep Brain Stimulation Targeting. 2698-2705 - Fei Zheng, Ping Yin, Kewei Liang, Tao Liu, Yujian Wang, Wenhan Hao, Qi Hao, Nan Hong:
Comparison of Different Fusion Radiomics for Predicting Benign and Malignant Sacral Tumors: A Pilot Study. 2415-2427 - Hao-Yang Chou, Yung-Chieh Lin, Sun-Yuan Hsieh, Hsin-Hung Chou, Cheng-Shih Lai, Bow Wang, Yi-Shan Tsai:
Deep Learning Model for Prediction of Bronchopulmonary Dysplasia in Preterm Infants Using Chest Radiographs. 2063-2073 - Koichiro Yasaka, Shunichi Uehara, Shimpei Kato, Yusuke Watanabe, Taku Tajima, Hiroyuki Akai, Naoki Yoshioka, Masaaki Akahane, Kuni Ohtomo, Osamu Abe, Shigeru Kiryu:
Super-resolution Deep Learning Reconstruction Cervical Spine 1.5T MRI: Improved Interobserver Agreement in Evaluations of Neuroforaminal Stenosis Compared to Conventional Deep Learning Reconstruction. 2466-2473 - Ernesto Diaz, Renuka Sriram, Jeremy W. Gordon, Avantika Sinha, Xiaoxi Liu, Sule I. Sahin, Jason C. Crane, Marram P. Olson, Hsin-Yu Chen, Jenna M. L. Bernard, Daniel B. Vigneron, Zhen Jane Wang, Duan Xu, Peder E. Z. Larson:
Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI. 2627-2634 - Peilong Wang, Timothy L. Kline, Andy D. Missert, Cole J. Cook, Matthew R. Callstrom, Alex Chan, Robert P. Hartman, Zachary S. Kelm, Panagiotis Korfiatis:
A Classification-Based Adaptive Segmentation Pipeline: Feasibility Study Using Polycystic Liver Disease and Metastases from Colorectal Cancer CT Images. 2186-2194 - Joseph H. Yacoub, Daniel A. Weitz, Thomas P. Stirrat, Allan Fong, Raj M. Ratwani:
Reading Room Interruptions are Less Disruptive When Using Asynchronous Communication Methods. 2038-2046 - Xing Lu, Yajun Ma, Eric Y. Chang, Jiyo S. Athertya, Hyungseok Jang, Saeed Jerban, Dana C. Covey, Susan Bukata, Christine B. Chung, Jiang Du:
Deep Convolutional Neural Network for Dedicated Regions-of-Interest Based Multi-Parameter Quantitative Ultrashort Echo Time (UTE) Magnetic Resonance Imaging of the Knee Joint. 2126-2134 - Eva Milara, Adolfo Gómez-Grande, Pilar Sarandeses, Alexander P. Seiffert, Enrique J. Gómez, Patricia Sánchez-González:
Automatic Skeleton Segmentation in CT Images Based on U-Net. 2390-2400 - Ilkay Yildiz Potter, Edward K. Rodriguez, Jim Wu, Ara Nazarian, Ashkan Vaziri:
An Automated Vertebrae Localization, Segmentation, and Osteoporotic Compression Fracture Detection Pipeline for Computed Tomographic Imaging. 2428-2443 - Yongchun You, Sihua Zhong, Guozhi Zhang, Yuting Wen, Dian Guo, Wanjiang Li, Zhenlin Li:
Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images. 2089-2098 - Xudong Guo, Lei Xu, Shengnan Li, Meidong Xu, Yuan Chu, Qinfen Jiang:
Cascade-EC Network: Recognition of Gastrointestinal Multiple Lesions Based on EfficientNet and CA_stm_Retinanet. 1-11 - S. Veluchamy, S. Sudharson, R. Annamalai, Zaid Bassfar, Amer Aljaedi, Sajjad Shaukat Jamal:
Automated Detection of COVID-19 from Multimodal Imaging Data Using Optimized Convolutional Neural Network Model. 2074-2088 - Maria Nazir, Sadia Shakil, Khurram Khurshid:
End-to-End Multi-task Learning Architecture for Brain Tumor Analysis with Uncertainty Estimation in MRI Images. 2149-2172 - Helene Koefoed-Nielsen, Kristian Kidholm, Marianne Harbo Frederiksen, Minne L. N. Mikkelsen:
Expectations and Experiences Among Clinical Staff Regarding Implementation of Digital Pathology: A Qualitative Study at Two Departments of Pathology. 2500-2512 - Ting-Wei Ou, Tzu-Chieh Weng, Ruey-Feng Chang:
A Novel Structure Fusion Attention Model to Detect Architectural Distortion on Mammography. 2227-2251 - Sanaz Vahdati, Bardia Khosravi, Elham Mahmoudi, Kuan Zhang, Pouria Rouzrokh, Shahriar Faghani, Mana Moassefi, Aylin Tahmasebi, Katherine P. Andriole, Peter Chang, Keyvan Farahani, Mona G. Flores, Les R. Folio, Sina Houshmand, Maryellen L. Giger, Judy W. Gichoya, Bradley J. Erickson:
A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey. 2015-2024 - Manikandan J, Jayashree K:
Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing. 2108-2125 - Luella Marcos, Paul S. Babyn, Javad Alirezaie:
Pure Vision Transformer (CT-ViT) with Noise2Neighbors Interpolation for Low-Dose CT Image Denoising. 2669-2687
Volume 37, Number 6, 2024
- Dawn Cram, Monief Eid, Mitchell M. Goldburgh, Jason Nagels, Laurence Yudkovitch, Alexander J. Towbin:
Report of the HIMSS-SIIM Enterprise Imaging Community Data Standards Evaluation Workgroup: Anatomic Ontology Assessment. 2709-2721 - Christopher J. Roth, Cheryl A. Petersilge, Dawn Cram, Kimberley M. Garriott, Louis M. Lannum, Cheryl K. Carey, Nikki Medina, Tammy Kwiatkoski, James T. Whitfill, Alexander J. Towbin:
Celebrating 10 Years of the HIMSS-SIIM Enterprise Imaging Community and Enterprise Imaging Informatics. 2722-2728 - Anish Raj, Ahmad Allababidi, Hany Kayed, Andreas L. H. Gerken, Julia Müller, Stefan O. Schönberg, Frank G. Zöllner, Johann S. Rink:
Streamlining Acute Abdominal Aortic Dissection Management - An AI-based CT Imaging Workflow. 2729-2739 - Prateek Bharadwaj, Michael Berger, Steven L. Blumer, Franziska Lobig:
Selecting the Best Radiology Workflow Efficiency Applications. 2740-2751 - Yubo Yuan, Lijun Liu, Xiaobing Yang, Li Liu, Qingsong Huang:
Multi-scale Lesion Feature Fusion and Location-Aware for Chest Multi-disease Detection. 2752-2767 - Mohammad Amin Sadeghi, Daniel Stevens, Shinjini Kundu, Rohan Sanghera, Richard Dagher, Vivek Yedavalli, Craig K. Jones, Haris I. Sair, Licia P. Luna:
Detecting Alzheimer's Disease Stages and Frontotemporal Dementia in Time Courses of Resting-State fMRI Data Using a Machine Learning Approach. 2768-2783 - Chunqing Zhou, Yi Xiao, Longxi Li, Yanyun Liu, Fubao Zhu, Weihua Zhou, Xiaoping Yi, Min Zhao:
Radiomics Nomogram Derived from Gated Myocardial Perfusion SPECT for Identifying Ischemic Cardiomyopathy. 2784-2793 - Thao Thi Phuong Dao, Tuan-Luc Huynh, Minh-Khoi Pham, Trung-Nghia Le, Tan-Cong Nguyen, Quang-Thuc Nguyen, Bich Anh Tran, Boi Ngoc Van, Chanh Cong Ha, Minh-Triet Tran:
Improving Laryngoscopy Image Analysis Through Integration of Global Information and Local Features in VoFoCD Dataset. 2794-2809 - Yongxin Guo, Yufeng Zhou:
Expansive Receptive Field and Local Feature Extraction Network: Advancing Multiscale Feature Fusion for Breast Fibroadenoma Segmentation in Sonography. 2810-2824 - Iqra Shahzadi, Tahir Mustafa Madni, Uzair Iqbal Janjua, Ghanwa Batool, Bushra Naz, Muhammad Qasim Ali:
CSAMDT: Conditional Self Attention Memory-Driven Transformers for Radiology Report Generation from Chest X-Ray. 2825-2837 - Lulu Wang, Wanqi Zhang, Wei Chen, Zhongshi He, Yuanyuan Jia, Jinglong Du:
Cross-Modality Reference and Feature Mutual-Projection for 3D Brain MRI Image Super-Resolution. 2838-2851 - Bin Song, Tingting Zheng, Hao Wang, Lang Tang, Xiaoli Xie, Qingyin Fu, Weiyan Liu, Pu-Yeh Wu, Mengsu Zeng:
Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI. 2852-2864 - Hongxia Li, Zhiling Liu, Fuyan Li, Yuwei Xia, Tong Zhang, Feng Shi, Qingshi Zeng:
Identification of Prolactinoma in Pituitary Neuroendocrine Tumors Using Radiomics Analysis Based on Multiparameter MRI. 2865-2873 - Kaifeng Gan, Yunpeng Liu, Ting Zhang, Dingli Xu, Leidong Lian, Zhe Luo, Jin Li, Liangjie Lu:
Deep Learning Model for Automatic Identification and Classification of Distal Radius Fracture. 2874-2882 - Yue Su, Xianwu Xia, Rong Sun, Jianjun Yuan, Qianjin Hua, Baosan Han, Jing Gong, Shengdong Nie:
Res-TransNet: A Hybrid deep Learning Network for Predicting Pathological Subtypes of lung Adenocarcinoma in CT Images. 2883-2894 - Baoyu Liang, Chao Tong, Jingying Nong, Yi Zhang:
Histological Subtype Classification of Non-Small Cell Lung Cancer with Radiomics and 3D Convolutional Neural Networks. 2895-2909 - Jia Sun, Zhilong Wang, Haitao Zhu, Qi Yang, Yingshi Sun:
Advanced Gastric Cancer: CT Radiomics Prediction of Lymph Modes Metastasis After Neoadjuvant Chemotherapy. 2910-2919 - Subhanik Purkayastha, Hrithwik Shalu, David Gutman, Andrei I. Holodny, Shakeel Modak, Ellen Basu, Brian Kushner, Kim Kramer, Sofia Haque, Joseph N. Stember:
Evolutionary Strategies AI Addresses Multiple Technical Challenges in Deep Learning Deployment: Proof-of-Principle Demonstration for Neuroblastoma Brain Metastasis Detection. 2920-2930 - Antoine Emin, Sophie Daubié, Loïc Gaillandre, Arthur Aouad, Jean-Baptiste Pialat, Valentin Favier, Florent Carsuzaa, Stéphane Tringali, Maxime Fieux:
Artificial Intelligence for Otosclerosis Detection: A Pilot Study. 2931-2939 - Mikel Carrilero-Mardones, Manuela Parras-Jurado, Alberto Nogales, Jorge Pérez-Martín, Francisco Javier Díez:
Deep Learning for Describing Breast Ultrasound Images with BI-RADS Terms. 2940-2954 - Md Mahfuz Al Hasan, Saba Ghazimoghadam, Padcha Tunlayadechanont, Mohammad Tahsin Mostafiz, Manas Gupta, Antika Roy, Keith Peters, Bruno Hochhegger, Anthony Mancuso, Navid Asadizanjani, Reza Forghani:
Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning. 2955-2966 - Ilkay Yildiz Potter, Diana Yeritsyan, Edward K. Rodriguez, Jim S. Wu, Ara Nazarian, Ashkan Vaziri:
Detection and Localization of Spine Disorders from Plain Radiography. 2967-2982 - Zhiyang Xu, Yanzi Miao, Guangxia Chen, Shiyu Liu, Hu Chen:
GLGFormer: Global Local Guidance Network for Mucosal Lesion Segmentation in Gastrointestinal Endoscopy Images. 2983-2995 - Alessio Fiorin, Carlos López Pablo, Marylène Lejeune, Ameer Hamza Siraj, Vincenzo Della Mea:
Enhancing AI Research for Breast Cancer: A Comprehensive Review of Tumor-Infiltrating Lymphocyte Datasets. 2996-3008 - Jason Belec, Justin Sutherland, Matthew Volpini, Kawan Rakhra, Dal Granville, Daniel J. La Russa, Teresa Flaxman, Eduardo Portela De Oliveira, Rafael Glikstein, Marlise P. dos Santos, Joel Werier, Miller MacPherson, Richard I Aviv, Vimoj Nair:
A Pilot Clinical and Technical Validation of an Immersive Virtual Reality Platform for 3D Anatomical Modeling and Contouring in Support of Surgical and Radiation Oncology Treatment Planning. 3009-3024 - Yi Wang, Wanying Yan, Yibo Feng, Fang Qian, Tiantian Zhang, Xin Huang, Dawei Wang, Maoneng Hu:
Deep Learning Models of Multi-Scale Lesion Perception Attention Networks for Diagnosis and Staging of Pneumoconiosis: A Comparative Study with Radiologists. 3025-3033 - Wenli Wang, Rongrong Sheng, Shumei Liao, Zifeng Wu, Linjun Wang, Cunming Liu, Chun Yang, Riyue Jiang:
LightGBM is an Effective Predictive Model for Postoperative Complications in Gastric Cancer: A Study Integrating Radiomics with Ensemble Learning. 3034-3048 - Jinxiu Yang, Zhen Wang, Huimin Wang, Peiyang Zheng, Wei Deng, Hui Gao, Kaixuan Yao, Yong Cheng, Mingkuan Wu, Rong He, Xiuzheng Yue, Yongqiang Yu, Ren Zhao, Xiaohu Li:
Myocardial Transit Time Mapping by CMR: A Novel Indicator of Microcirculatory Dysfunction in Cardiac Amyloidosis. 3049-3056 - Takuma Usuzaki, Ryusei Inamori, Mami Ishikuro, Taku Obara, Eichi Takaya, Noriyasu Homma, Kei Takase:
Predicting EGFR Status After Radical Nephrectomy or Partial Nephrectomy for Renal Cell Carcinoma on CT Using a Self-attention-based Model: Variable Vision Transformer (vViT). 3057-3069 - Koichiro Yasaka, Hiroyuki Akai, Shimpei Kato, Taku Tajima, Naoki Yoshioka, Toshihiro Furuta, Hajime Kageyama, Yui Toda, Masaaki Akahane, Kuni Ohtomo, Osamu Abe, Shigeru Kiryu:
Iterative Motion Correction Technique with Deep Learning Reconstruction for Brain MRI: A Volunteer and Patient Study. 3070-3076 - Laura R. Bramwell, Jack A. Spencer, Ryan Frankum, Emad Manni, Lorna W. Harries:
Image Analysis Using the Fluorescence Imaging of Nuclear Staining (FINS) Algorithm. 3077-3089 - Guobang Yu, Yi Zuo, Bin Wang, Hui Liu:
Prediction of Tumor-Associated Macrophages and Immunotherapy Benefits Using Weakly Supervised Contrastive Learning in Breast Cancer Pathology Images. 3090-3100 - Xiaoming Liu, Xiao Li, Ying Zhang, Man Wang, Junping Yao, Jinshan Tang:
Boundary-Repairing Dual-Path Network for Retinal Layer Segmentation in OCT Image with Pigment Epithelial Detachment. 3101-3130 - Hao Zhou, Wenhan Yang, Limei Sun, Li Huang, Songshan Li, Xiaoling Luo, Yili Jin, Wei Sun, Wenjia Yan, Jing Li, Xiaoyan Ding, Yao He, Zhi Xie:
RDLR: A Robust Deep Learning-Based Image Registration Method for Pediatric Retinal Images. 3131-3145 - Rabia Karakus, Muhammet Üsame Öziç, Melek Tassoker:
AI-Assisted Detection of Interproximal, Occlusal, and Secondary Caries on Bite-Wing Radiographs: A Single-Shot Deep Learning Approach. 3146-3159 - Surong Chen, Yan Yang, Weiwei Wu, Ruonan Wei, Zezhou Wang, Franklin R. Tay, Jingyu Hu, Jingzhi Ma:
Classification of Caries Based on CBCT: A Deep Learning Network Interpretability Study. 3160-3173 - Ishak Paçal, Melek Alaftekin, Ferhat D. Zengul:
Enhancing Skin Cancer Diagnosis Using Swin Transformer with Hybrid Shifted Window-Based Multi-head Self-attention and SwiGLU-Based MLP. 3174-3192 - Zhiming Cheng, Shuai Wang, Yuhan Gao, Zunjie Zhu, Chenggang Yan:
Invariant Content Representation for Generalizable Medical Image Segmentation. 3193-3207 - Joseph D. Sobek, Jose R. Medina Inojosa, Betsy J. Medina Inojosa, S. M. Rassoulinejad-Mousavi, Gian Marco Conte, Francisco Lopez-Jimenez, Bradley J. Erickson:
MedYOLO: A Medical Image Object Detection Framework. 3208-3216 - Hossein Arabi, Habib Zaidi:
Contrastive Learning vs. Self-Learning vs. Deformable Data Augmentation in Semantic Segmentation of Medical Images. 3217-3230 - John D. Mayfield, Ryan Murtagh, John Ciotti, Derrick Robertson, Issam El Naqa:
Time-Dependent Deep Learning Prediction of Multiple Sclerosis Disability. 3231-3249 - Pranav Kulkarni, Adway U. Kanhere, Eliot L. Siegel, Paul H. Yi, Vishwa S. Parekh:
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging. 3250-3263 - Jianning Chi, Jian Miao, Jia-hui Chen, Huan Wang, Xiaosheng Yu, Ying Huang:
DSTAN: A Deformable Spatial-temporal Attention Network with Bidirectional Sequence Feature Refinement for Speckle Noise Removal in Thyroid Ultrasound Video. 3264-3281 - Sheikh Burhan Ul Haque, Aasim Zafar:
Removing Adversarial Noise in X-ray Images via Total Variation Minimization and Patch-Based Regularization for Robust Deep Learning-based Diagnosis. 3282-3303 - Andreas Michael Bucher, Jan Egger, Julia Dietz, Ralph Strecker, Tom Hilbert, Eric Frodl, Mike Wenzel, Tobias Penzkofer, Bernd Hamm, Felix Kh Chun, Thomas J. Vogl, Jens Kleesiek, Martin Beeres:
Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer. 3304-3315
Volume 37, Number S1, 2024
- Scientific Abstracts from the 2024 Conference on Machine Intelligence in Medical Imaging (CMIMI) of the Society for Imaging Informatics in Medicine (SIIM). 1-35
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