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Computer-Aided Diagnosis 2020: Houston, TX, USA
- Horst K. Hahn, Maciej A. Mazurowski:
Medical Imaging 2020: Computer-Aided Diagnosis, Houston, TX, USA, February 16-19, 2020. SPIE Proceedings 11314, SPIE 2020, ISBN 9781510633957
Mammography
- Stefano Pedemonte:
A hypersensitive breast cancer detector (Conference Presentation). - Yifan Peng
, Rui Hou, Yinhao Ren, Lars J. Grimm, Jeffrey R. Marks, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Microcalcification localization and cluster detection using unsupervised convolutional autoencoders and structural similarity index. - Alexej Gossmann
, Kenny H. Cha, Xudong Sun:
Performance deterioration of deep neural networks for lesion classification in mammography due to distribution shift: an analysis based on artificially created distribution shift. - Rui Hou, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
A multitask deep learning method in simultaneously predicting occult invasive disease in ductal carcinoma in-situ and segmenting microcalcifications in mammography. - Sadanand Singh, Thomas Paul Matthews, Meet Shah, Brent Mombourquette, Trevor Tsue, Aaron Long, Ranya Almohsen, Stefano Pedemonte, Jason Su:
Adaptation of a deep learning malignancy model from full-field digital mammography to digital breast tomosynthesis.
Chest I
- Angshuman Paul
, Yuxing Tang, Ronald M. Summers:
Fast few-shot transfer learning for disease identification from chest x-ray images using autoencoder ensemble. - Anindo Saha
, Fakrul Islam Tushar
, Khrystyna Faryna, Vincent M. D'Anniballe
, Rui Hou, Maciej A. Mazurowski, Geoffrey D. Rubin
, Joseph Y. Lo:
Weakly supervised 3D classification of chest CT using aggregated multi-resolution deep segmentation features. - Jia Liang, Yuxing Tang, Youbao Tang, Jing Xiao, Ronald M. Summers:
Bone suppression on chest radiographs with adversarial learning. - Jordan D. Fuhrman, Rowena Yip, Artit C. Jirapatnakul
, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger:
Cascade of U-Nets in the detection and classification of coronary artery calcium in thoracic low-dose CT. - Simon Rennotte, Pierre-Yves Brillet
, Catalin I. Fetita:
Comparison of CNN architectures and training strategies for quantitative analysis of idiopathic interstitial pneumonia. - Jennie Crosby, Thomas Rhines, Feng Li, Heber MacMahon, Maryellen L. Giger:
Deep learning for pneumothorax detection and localization using networks fine-tuned with multiple institutional datasets.
Neuro I
- Arko Barman
, Victor Lopez-Rivera, Songmi Lee, Farhaan S. Vahidy, James Z. Fan, Sean I. Savitz, Sunil A. Sheth, Luca Giancardo
:
Combining symmetric and standard deep convolutional representations for detecting brain hemorrhage. - Mina Rezaei, Tomoki Uemura, Janne Näppi, Hiroyuki Yoshida, Christoph Lippert, Christoph Meinel:
Generative synthetic adversarial network for internal bias correction and handling class imbalance problem in medical image diagnosis. - Mikhail Milchenko, Pamela LaMontagne, Daniel S. Marcus:
Automatic detection of contrast enhancement in T1-weighted brain MRI of human adults. - Takuya Fuchigami, Sadato Akahori, Takayuki Okatani, Yuanzhong Li:
A hyperacute stroke segmentation method using 3D U-Net integrated with physicians' knowledge for NCCT. - Linmin Pei
, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin:
Deep learning with context encoding for semantic brain tumor segmentation and patient survival prediction.
Abdomen
- Chenglong Wang, Masahiro Oda
, Kensaku Mori:
Organ segmentation from full-size CT images using memory-efficient FCN. - Sai Aditya Sriram, Angshuman Paul
, Yingying Zhu, Veit Sandfort, Perry J. Pickhardt, Ronald M. Summers:
Multilevel UNet for pancreas segmentation from non-contrast CT scans through domain adaptation. - Li Liu, Jiang Tian, Cheng Zhong, Zhongchao Shi, Feiyu Xu:
Robust hepatic vessels segmentation model based on noisy dataset. - Amogh Hiremath, Rakesh Shiradkar, Nathaniel Braman, Prateek Prasanna
, Ardeshir R. Rastinehad, Andrei S. Purysko, Anant Madabhushi:
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. - Marc Jason Pomeroy, Yi Wang, Anushka Banerjee, Almas F. Abbasi, Matthew A. Barish, Edward Sun, Juan Carlos Bucobo, Perry J. Pickhardt, Zhengrong Liang:
Integration of optical and virtual colonoscopy images for enhanced classification of colorectal polyps.
Musculoskeletal
- Daniel C. Elton
, Veit Sandfort, Perry J. Pickhardt, Ronald M. Summers:
Accurately identifying vertebral levels in large datasets. - Jimin Tan, Bofei Zhang, Kyunghyun Cho, Gregory Chang, Cem M. Deniz:
Semi-supervised learning for predicting total knee replacement with unsupervised data augmentation. - Yan Wu
, Yajun Ma, Jiang Du, Lei Xing
:
Deciphering tissue relaxation parameters from a single MR image using deep learning. - Nianyi Li, Albert Swiecicki, Nicholas Said, Jonathan O'Donnell, William A. Jiranek, Maciej A. Mazurowski:
Automatic Kellgren-Lawrence grade estimation driven deep learning algorithms. - Jakub Ceranka, Frédéric Lecouvet, Johan de Mey
, Jef Vandemeulebroucke
:
Computer-aided detection of focal bone metastases from whole-body multi-modal MRI.
Radiomics
- Tomoki Uemura, Chinatsu Watari, Janne J. Näppi, Toru Hironaka, Hyoungseop Kim, Hiroyuki Yoshida:
U-radiomics for predicting survival of patients with idiopathic pulmonary fibrosis. - Joseph J. Foy, Inna H. Gertsenshteyn
, Hania A. Al-Hallaq
, Samuel G. Armato III, William F. Sensakovic:
Dependence of radiomics features on CT image acquisition and reconstruction parameters using a cadaveric liver. - Amrish Selvam, Jacob Antunes, Kaustav Bera, Asya Ofshteyn, Justin T. Brady, Katherine Bingmer, Kenneth Friedman, Sharon L. Stein, Rajmohan Paspulati, Andrei S. Purysko, Matthew Kalady, Anant Madabhushi, Satish E. Viswanath
:
Multi-site evaluation of stable radiomic features for more accurate evaluation of pathologic downstaging on MRI after chemoradiation for rectal cancers. - Raymond Joseph Acciavatti, Eric A. Cohen, Omid Haji Maghsoudi, Aimilia Gastounioti, Lauren Pantalone, Meng-Kang Hsieh, Emily F. Conant, Christopher G. Scott, Stacey J. Winham, Karla Kerlikowske, Celine Vachon, Andrew D. A. Maidment, Despina Kontos:
Robust radiomic feature selection in digital mammography: understanding the effect of imaging acquisition physics using phantom and clinical data analysis. - Heather M. Whitney, Maryellen L. Giger:
Improvement of classification performance using harmonization across field strength of radiomic features extracted from DCE-MR images of the breast. - Sehwa Moon, Dahim Choi, Ji-Yeon Lee, Myoung-Hee Kim, Helen Hong, Bong-Seog Kim, Jang-Hwan Choi:
Machine learning-powered prediction of recurrence in patients with non-small cell lung cancer using quantitative clinical and radiomic biomarkers.
Breast MRI, Skin
- Zachary Papanastasopoulos, Ravi K. Samala
, Heang-Ping Chan
, Lubomir M. Hadjiiski, Chintana Paramagul, Mark A. Helvie, Colleen H. Neal:
Explainable AI for medical imaging: deep-learning CNN ensemble for classification of estrogen receptor status from breast MRI. - Karen Drukker
, Alexandra Edwards, John Papaioannou, Maryellen L. Giger:
Deep learning predicts breast cancer recurrence in analysis of consecutive MRIs acquired during the course of neoadjuvant chemotherapy. - Qiyuan Hu
, Heather M. Whitney, Maryellen L. Giger:
Using ResNet feature extraction in computer-aided diagnosis of breast cancer on 927 lesions imaged with multiparametric MRI. - Bas H. M. van der Velden, Max A. A. Ragusi, Markus H. A. Janse, Claudette E. Loo, Kenneth G. A. Gilhuijs
:
Interpretable deep learning regression for breast density estimation on MRI. - Gourav Modanwal
, Adithya Vellal, Mateusz Buda, Maciej A. Mazurowski:
MRI image harmonization using cycle-consistent generative adversarial network. - Nils Gessert, Marcel Bengs, Alexander Schlaefer
:
Melanoma detection with electrical impedance spectroscopy and dermoscopy using joint deep learning models. - Hamidullah Binol, M. Khalid Khan Niazi, Alisha Plotner, Jennifer Sopkovich, Benjamin Kaffenberger
, Metin N. Gurcan
:
A multidimensional scaling and sample clustering to obtain a representative subset of training data for transfer learning-based rosacea lesion identification.
Breast
- Ravi K. Samala
, Heang-Ping Chan
, Lubomir M. Hadjiiski, Sathvik Koneru:
Hazards of data leakage in machine learning: a study on classification of breast cancer using deep neural networks. - Yue Li, Zheng Xie, Zilong He, Xiangyuan Ma, Yanhui Guo, Weiguo Chen, Yao Lu:
Architectural distortion detection approach guided by mammary gland spatial pattern in digital breast tomosynthesis. - Juhun Lee, Robert M. Nishikawa
:
Simulating breast mammogram using conditional generative adversarial network: application towards finding mammographically-occult cancer. - Chanho Kim, Won Hwa Kim, Hye Jung Kim, Jaeil Kim:
Weakly-supervised US breast tumor characterization and localization with a box convolution network. - Emine Doganay, Yahong Luo, Long Gao, Puchen Li, Wendie A. Berg, Shandong Wu:
Performance comparison of different loss functions for digital breast tomosynthesis classification using 3D deep learning model.
Chest II, Lymph Nodes
- Heike Carolus, Andra-Iza Iuga, Tom Brosch, Rafael Wiemker, Frank Thiele, Anna J. Höink, David Maintz, Michael Püsken, Tobias Klinder:
Automated detection and segmentation of mediastinal and axillary lymph nodes from CT using foveal fully convolutional networks. - Hidir Cem Altun, Grzegorz Chlebus, Colin Jacobs
, Hans Meine, Bram van Ginneken
, Horst K. Hahn:
Feasibility of end-to-end trainable two-stage U-Net for detection of axillary lymph nodes in contrast-enhanced CT based on sparse annotations. - Xiaomeng Gu, Weiyang Xie, Qiming Fang, Jun Zhao, Qiang Li:
Lung vessel suppression and its effect on nodule detection in chest CT scans. - Yifan Wang, Chuan Zhou, Heang-Ping Chan
, Lubomir M. Hadjiiski, Jun Wei, Aamer Chughtai, Ella A. Kazerooni:
Hybrid deep-learning model for volume segmentation of lung nodules in CT images. - Rohan Abraham, Ian Janzen, Saeed Seyyedi, Sukhinder Khattra, John Mayo, Ren Yuan, Renelle Myers, Stephen Lam, Calum E. MacAulay:
Machine learning and deep learning approaches for classification of sub-cm lung nodules in CT scans (Conference Presentation). - Yannan Lin
, Leihao Wei
, Simon X. Han, Denise R. Aberle, William Hsu
:
EDICNet: An end-to-end detection and interpretable malignancy classification network for pulmonary nodules in computed tomography.
Keynote and Methodology
- Jonathan Wiener:
Will AI make me a better doctor? (Conference Presentation). - Vatsal Agarwal, Youbao Tang, Jing Xiao, Ronald M. Summers:
Weakly-supervised lesion segmentation on CT scans using co-segmentation. - Mehdi Moradi, Ken C. L. Wong, Alexandros Karargyris, Tanveer F. Syeda-Mahmood:
Quality controlled segmentation to aid disease detection.
Head and neck, eye
- Marcel Bengs, Stephan Westermann, Nils Gessert, Dennis Eggert, Andreas O. H. Gerstner, Nina A. Müller, Christian Betz, Wiebke Laffers, Alexander Schlaefer
:
Spatio-spectral deep learning methods for in-vivo hyperspectral laryngeal cancer detection. - Hamidullah Binol, Aaron C. Moberly, M. Khalid Khan Niazi, Garth Essig, Jay Shah, Charles Elmaraghy, Theodoros Teknos, Nazhat Taj-Schaal, Lianbo Yu, Metin N. Gurcan
:
Decision fusion on image analysis and tympanometry to detect eardrum abnormalities. - Friso G. Heslinga
, Josien P. W. Pluim, A. J. H. M. Houben, Miranda T. Schram, Ronald M. A. Henry, Coen D. A. Stehouwer
, Marleen J. van Greevenbroek
, Tos T. J. M. Berendschot
, Mitko Veta:
Direct classification of type 2 diabetes from retinal fundus images in a population-based sample from the Maastricht study. - Timo Kepp, Helge Sudkamp, Claus von der Burchard, Hendrik Schenke, Peter Koch, Gereon Hüttmann, Johann Roider, Mattias P. Heinrich
, Heinz Handels
:
Segmentation of retinal low-cost optical coherence tomography images using deep learning.
Novel Applications
- Khrystyna Faryna, Fakrul Islam Tushar
, Vincent M. D'Anniballe
, Rui Hou, Geoffrey D. Rubin
, Joseph Y. Lo:
Attention-guided classification of abnormalities in semi-structured computed tomography reports. - Feng Yang, Nicolas Quizon, Hang Yu, Kamolrat Silamut, Richard James Maude
, Stefan Jaeger, Sameer K. Antani:
Cascading YOLO: automated malaria parasite detection for Plasmodium vivax in thin blood smears. - Maysam Shahedi
, James D. Dormer
, T. T. Anusha Devi, Quyen N. Do
, Yin Xi
, Matthew A. Lewis, Ananth J. Madhuranthakam, Diane M. Twickler, Baowei Fei
:
Segmentation of uterus and placenta in MR images using a fully convolutional neural network. - Jiaxing Tan, Shu Zhang, Weiguo Cao, Yongfeng Gao, Lihong Li, Yumei Huo, Zhengrong Liang:
A multi-stage fusion strategy for multi-scale GLCM-CNN model in differentiating malignant from benign polyps. - Daniel Hoklai Chapman-Sung, Lubomir M. Hadjiiski, Dhanuj Gandikota, Heang-Ping Chan
, Ravi Samala
, Elaine M. Caoili, Richard H. Cohan
, Alon Z. Weizer, Ajjai Alva, Chuan Zhou:
Convolutional neural network-based decision support system for bladder cancer staging in CT urography: decision threshold estimation and validation.
Neuro II
- Seyed Saman Saboksayr, John J. Foxe, Axel Wismüller:
Attention-deficit/hyperactivity disorder prediction using graph convolutional networks. - Mariana Pereira, Irene Fantini, Roberto A. Lotufo
, Letícia Rittner
:
An extended-2D CNN for multiclass Alzheimer's Disease diagnosis through structural MRI. - Yashas Hiremath, Marwa Ismail, Ruchika Verma
, Jacob Antunes, Pallavi Tiwari:
Combining deep and hand-crafted MRI features for identifying sex-specific differences in autism spectrum disorder versus controls. - Tsubasa Goto, Caihua Wang, Yuanzhong Li, Yukihiro Tsuboshita:
Multi-modal deep learning for predicting progression of Alzheimer's disease using bi-linear shake fusion. - Axel Wismüller, John J. Foxe, Paul Geha, Seyed Saman Saboksayr:
Large-scale Extended Granger Causality (lsXGC) for classification of Autism Spectrum Disorder from resting-state functional MRI. - Rita Lai, Daniela Schenone
, Gianmario Sambuceti, Anna Maria Massone, Cristina Campi
, Adriano Chiò
, Claudia Caponnetto, Angelina Cistaro, Matteo Bauckneht
, Vanessa Cossu, Silvia Morbelli, Cecilia Marini, Michele Piana:
Prognostic power of the human psoas muscles FDG metabolism in amyotrophic lateral sclerosis.
Poster Session
- Basel Alyafi
, Oliver Díaz
, Robert Marti
:
DCGANs for realistic breast mass augmentation in x-ray mammography. - Michael Vieceli, Amy Van Dusen, Karen Drukker
, Hiroyuki Abe, Maryellen L. Giger, Heather M. Whitney:
Case-based repeatability of machine learning classification performance on breast MRI. - Peter S. Carras, Carina Pereira, Debosmita Biswas, Christoph I. Lee, Savannah C. Partridge, Adam M. Alessio:
Genetic algorithm for machine learning architecture selection for breast MRI classification. - Stijn De Buck
, Jeroen Bertels
, Chelsey Vanbilsen, Tanguy Dewaele, Chantal Van Ongeval
, Hilde Bosmans
, Jan Vandevenne, Paul Suetens:
Automated breast cancer risk estimation on routine CT thorax scans by deep learning segmentation. - Erick Rodríguez-Esparza
, Laura A. Zanella-Calzada, Diego Oliva
, Marco Pérez-Cisneros:
Automatic detection and classification of abnormal tissues on digital mammograms based on a bag-of-visual-words approach. - Yuanpin Zhou
, Jun Wei, Mark A. Helvie, Heang-Ping Chan
, Chuan Zhou, Lubomir M. Hadjiiski, Yao Lu:
Generating high resolution digital mammogram from digitized film mammogram with conditional generative adversarial network. - Albert Swiecicki, Mateusz Buda, Ashirbani Saha, Nianyi Li, Sujata V. Ghate, Ruth Walsh
, Maciej A. Mazurowski:
Generative adversarial network-based image completion to identify abnormal locations in digital breast tomosynthesis images. - William Funke, Benjamin Veasey, Jacek M. Zurada, Hichem Frigui, Amir A. Amini:
3D U-Net for segmentation of pulmonary nodules in volumetric CT scans from multi-annotator truth estimation. - Yuki Suzuki, Kazuki Yamagata, Yanagawa Masahiro
, Shoji Kido, Noriyuki Tomiyama:
Weak supervision in convolutional neural network for semantic segmentation of diffuse lung diseases using partially annotated dataset. - Colin B. Hansen, Yiyuan Zhao, Halid Ziya Yerebakan, Luca Bogoni, Anna K. Jerebko:
False positive reduction of vasculature for pulmonary nodule detection. - Hengtao Guo
, Melanie Krüger, Ge Wang
, Mannudeep K. Kalra, Pingkun Yan:
Multi-task learning for mortality prediction in LDCT images. - Hidenobu Suzuki
, Mikio Matsuhiro, Yoshiki Kawata, Noboru Niki, Issei Imoto, Yasutaka Nakano, Masahiko Kusumoto, Masahiro Kaneko:
Association analysis of SNPs with CT image-based phenotype of emphysema progression in heavy smokers. - Phuong Nguyen, David Chapman, Sumeet Menon, Michael Morris
, Yelena Yesha:
Active semi-supervised expectation maximization learning for lung cancer detection from Computerized Tomography (CT) images with minimally label training data. - Panagiotis Gonidakis
, Bart Jansen
, Jef Vandemeulebroucke
:
Artificially augmenting data or adding more samples? A study on a 3D CNN for lung nodule classification. - Babak Haghighi, Peter B. Noël, Eric A. Cohen, Lauren Pantalone, Anil Vachani, Katharine A. Rendle
, Jocelyn Wainwright, Chelsea Saia, Eduardo Jose Mortani Barbosa Jr., Despina Kontos:
Assessment of CT image reconstruction parameters on radiomic features in a lung cancer screening cohort: the PROSPR study. - Ryan Sullivan, Gregory Holste
, Jonathan Burkow, Adam M. Alessio
:
Deep learning methods for segmentation of lines in pediatric chest radiographs. - Takeru Kageyama, Yoshiki Kawata, Noboru Niki, Masahiko Kusumoto, Yoshiki Aokage, Genichiro Ishii, Hironobu Ohmatsu, Takaaki Tsuchida, Yuji Matsumoto, Kenji Eguchi, Masahiro Kaneko:
Differential diagnosis of pulmonary nodules using 3D CT images. - Jorie D. Budzikowski, Ahmed A. Rashid, Joseph J. Foy, Jonathan H. Chung, Imre Noth, Samuel G. Armato III:
Radiomics-based texture analysis of idiopathic pulmonary fibrosis for genetic and survival predictions. - Sohyun Byun, Julip Jung, Helen Hong, Hoonil Oh, Bong-seog Kim:
Lung tumor segmentation using coupling-net with shape-focused prior on chest CT images of non-small cell lung cancer patients. - Dong Wei, Yiming Li, Yinyan Wang, Tianyi Qian, Yefeng Zheng
:
Deep convolutional neural networks for molecular subtyping of gliomas using magnetic resonance imaging. - Mohammad Mahdi Shiraz Bhurwani
, Mohammad Waqas, Kyle A. Williams, Ryan A. Rava, Alexander R. Podgorsak, Kenneth V. Snyder, Elad I. Levy, Jason M. Davies, Adnan H. Siddiqui, Ciprian N. Ionita:
Predicting treatment outcome of intracranial aneurysms using angiographic parametric imaging and recurrent neural networks. - Jorge Orozco-Sanchez
, José G. Tamez-Peña
:
Prediction of MCI to AD risk of conversion survival models: qMRI vs CSF measures and cognitive assessments. - Haolun Li, Rui Zong, Xin Xu, Longsheng Pan, Qionghai Dai, Feng Xu, Hao Gao, Wensheng Wang:
Diagnosis of Parkinson's Disease with a hybrid feature selection algorithm based on a discrete artificial bee colony. - Evan D. H. Gates, Jonathan S. Lin, Jeffrey S. Weinberg, Sujit S. Prabhu, Jackson Hamilton
, John D. Hazle, Gregory N. Fuller, Veera Baladandayuthapani, David T. Fuentes, Dawid Schellingerhout:
Advanced magnetic resonance imaging based algorithm for local grading of glioma. - Ronald M. Juarez-Chambi, Carmen Kut, Kaisorn L. Chaichana, Alfredo Quinones-Hinojosa, Xingde Li, Javier A. Jo:
Neural networks for in situ detection of glioma infiltration using optical coherence tomography. - Hooman Rokham
, Haleh Falakshahi
, Vince D. Calhoun
:
A data-driven approach for stratifying psychotic and mood disorders subjects using structural magnitude resonance imaging data. - Tatsat R. Patel
, Nikhil Paliwal
, Prakhar Jaiswal, Mohammad Waqas, Maxim Mokin, Adnan H. Siddiqui, Hui Meng, Rahul Rai, Vincent M. Tutino:
Multi-resolution CNN for brain vessel segmentation from cerebrovascular images of intracranial aneurysm: a comparison of U-Net and DeepMedic. - Yang Lei
, Zhen Tian, Shannon Kahn, Walter J. Curran, Tian Liu, Xiaofeng Yang
:
Automatic detection of brain metastases using 3D mask R-CNN for stereotactic radiosurgery. - Yabo Fu, Yang Lei
, Tonghe Wang
, Xiaojun Jiang, Walter J. Curran, Tian Liu, Hui-Kuo Shu, Xiaofeng Yang
:
Automatic brain arteriovenous malformations segmentation on contrast CT images using combined region proposal network and V-Net. - Min Jin Lee, Helen Hong, Kyu Won Shim
:
Computer-assisted quantification of surgical outcome in infants with sagittal craniosynostosis in 3D head CT images using mean normal skull model. - Ramon Correa, Qiu Lei, Jonathan Chen
, Johnathan Zeng, Jennifer Yu, Pallavi Tiwari:
"Lesion-habitat" radiomics to distinguish radiation necrosis from tumor recurrence on post-treatment MRI in metastatic brain tumors. - Joost van der Putten, Jeroen de Groof, Fons van der Sommen
, Maarten R. Struyvenberg, Svitlana Zinger, Wouter L. Curvers, Erik J. Schoon, Jacques J. Bergman
, Peter H. N. de With:
First steps into endoscopic video analysis for Barrett's cancer detection: challenges and opportunities. - Pritesh Mehta, Michela Antonelli, Hashim Uddin Ahmed, Mark Emberton, Shonit Punwani, Sébastien Ourselin
:
Decision fusion of 3D convolutional neural networks to triage patients with suspected prostate cancer using volumetric biparametric MRI. - Hirohisa Oda, Kohei Nishio, Takayuki Kitasaka, Hizuru Amano, Aitaro Takimoto, Hiroo Uchida
, Kojiro Suzuki, Hayato Itoh, Masahiro Oda
, Kensaku Mori:
Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images. - Tomoki Uemura, Janne J. Näppi, Toru Hironaka, Hyoungseop Kim, Hiroyuki Yoshida:
Comparative performance of 3D-DenseNet, 3D-ResNet, and 3D-VGG models in polyp detection for CT colonography. - Binu Enchakolody, Brianna Henderson, Stewart C. Wang
, Grace L. Su
, Ashish P. Wasnik, Mahmoud M. Al-Hawary, Ryan W. Stidham:
Machine learning methods to predict presence of intestine damage in patients with Crohn's disease. - Levi Verhage, Joost van der Putten, Fons van der Sommen
, Jeroen de Groof, Maarten R. Struyvenberg, Peter H. N. de With:
The field effect in Barrett's Esophagus: a macroscopic view using white light endoscopy and deep learning. - Hayato Itoh, Zhongyang Lu, Yuichi Mori, Masashi Misawa, Masahiro Oda
, Shin-ei Kudo, Kensaku Mori:
Visualising decision-reasoning regions in computer-aided pathological pattern diagnosis of endoscytoscopic images based on CNN weights analysis. - Lili Wang, Jie Wu, Guang Yang, Bin Zheng:
Computer-aided staging of gastric cancer using radiomics signature on computed tomography imaging.