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ORCID15th MLMI@MICCAI 2024: Marrakesh, Morocco - Part I
- Xuanang Xu
, Zhiming Cui, Islem Rekik, Xi Ouyang, Kaicong Sun:
Machine Learning in Medical Imaging - 15th International Workshop, MLMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings, Part I. Lecture Notes in Computer Science 15241, Springer 2025, ISBN 978-3-031-73283-6 - Koushik Biswas, Ridam Pal, Shaswat Patel, Debesh Jha, Meghana Karri, Amit Reza, Gorkem Durak, Alpay Medetalibeyoglu, Matthew Antalek, Yury Velichko, Daniela P. Ladner, Amir Borhani, Ulas Bagci:
A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation. 1-11 - Jiaqi Qu, Xunbin Wei, Xiaohua Qian:
Generalizable Lymph Node Metastasis Prediction in Pancreatic Cancer. 12-21 - Haoyuan Chen, Yonghao Li, Jiadong Zhang, Qi Xu, Meiyu Li, Zhenhui Li, Xuejun Qian, Dinggang Shen:
IRUM: An Image Representation and Unified Learning Method for Breast Cancer Diagnosis from Multi-View Ultrasound Images. 22-30 - Ruochen Li, Jiazhen Pan, Youxiang Zhu, Juncheng Ni, Daniel Rueckert:
Classification, Regression and Segmentation Directly from K-Space in Cardiac MRI. 31-41 - Zhenyu Bu, Yang Liu, Jiayu Huo, Jingjing Peng, Kaini Wang, Guangquan Zhou, Rachel Sparks, Prokar Dasgupta, Alejandro Granados, Sébastien Ourselin:
DDSB: An Unsupervised and Training-Free Method for Phase Detection in Echocardiography. 42-51 - Zhe Liu, Xiliang Zhu, Tong Han, Yuhao Huang, Jian Wang, Lian Liu, Fang Wang, Dong Ni, Zhongshan Gou, Xin Yang:
Mitral Regurgitation Recogniton Based on Unsupervised Out-of-Distribution Detection with Residual Diffusion Amplification. 52-62 - Jongum Yoon, Sunghee Jung, Byunghwan Jeon:
Deep Reinforcement Learning with Multiple Centerline-Guidance for Localization of Left Atrial Appendage Orifice from CT Images. 63-72 - Furqan Shaukat, Syed Muhammad Anwar, Abhijeet Parida, Van Khanh Lam, Marius George Linguraru, Lubdha M. Shah:
Lung-CADex: Fully Automatic Zero-Shot Detection and Classification of Lung Nodules in Thoracic CT Images. 73-82 - Caiwen Jiang, Xiaodan Xing, Zaixin Ou, Mianxin Liu, Simon Walsh, Guang Yang, Dinggang Shen:
CIResDiff: A Clinically-Informed Residual Diffusion Model for Predicting Idiopathic Pulmonary Fibrosis Progression. 83-93 - Darshana Govind, Zijun Gao, Chaitanya Parmar, Kenneth Broos, Nicholas Fountoulakis, Lenore Noonan, Shinobu Yamamoto, Natalia Zemlianskaia, Craig S. Meyer, Emily Scherer, Michael Deman, Pablo F. Damasceno, Philip S. Murphy, Terence Rooney, Elizabeth Hsia, Anna Beutler, Robert L. Janiczek, Stephen S. F. Yip, Kristopher Standish:
Vision Transformer Model for Automated End-to-End Radiographic Assessment of Joint Damage in Psoriatic Arthritis. 94-103 - Wenxuan Wu, Tong Xiong, Dongzi Shi, Ruowen Qu, Xiangmin Xu, Xiaofen Xing, Xin Zhang:
CorticalEvolve: Age-Conditioned Ordinary Differential Equation Model for Cortical Surface Reconstruction. 104-113 - Ruoyou Wu, Jian Cheng, Cheng Li, Juan Zou, Jing Yang, Wenxin Fan, Yong Liang, Shanshan Wang:
CSR-dMRI: Continuous Super-Resolution of Diffusion MRI with Anatomical Structure-Assisted Implicit Neural Representation Learning. 114-123 - Jan Kybic, David Pakizer, Jirí Kozel, Patricie Michalcová, Frantisek Charvát, David Skoloudík:
Atherosclerotic Plaque Stability Prediction from Longitudinal Ultrasound Images. 124-132 - Yuping Wang, Dongdong Sun, Jun Shi, Wei Wang, Zhi-Guo Jiang, Haibo Wu, Yushan Zheng:
Leveraging IHC Staining to Prompt HER2 Status Prediction from HE-Stained Histopathology Whole Slide Images. 133-142 - Shikha Dubey, Yosep Chong, Beatrice Knudsen, Shireen Y. Elhabian:
VIMs: Virtual Immunohistochemistry Multiplex Staining via Text-to-Stain Diffusion Trained on Uniplex Stains. 143-155 - Zhaoxiang Wu, Biao Jie, Wen Li, Wentao Jiang, Yang Yang, Tongchun Du:
Structural-Connectivity-Guided Functional Connectivity Representation for Multi-modal Brain Disease Classification. 156-165 - Runqi Wang, Zehong Cao, Yichu He, Jiameng Liu, Feng Shi, Dinggang Shen:
Clinical Brain MRI Super-Resolution with 2D Slice-Wise Diffusion Model. 166-176 - Xiaohan Xing, Liang Qiu, Lequan Yu, Lingting Zhu, Lei Xing, Lianli Liu:
Low-to-High Frequency Progressive K-Space Learning for MRI Reconstruction. 177-186 - Hemant Kumar Aggarwal, Sudhanya Chatterjee, Dattesh Shanbhag, Uday Patil, K. V. S. Hari:
LSST: Learned Single-Shot Trajectory and Reconstruction Network for MR Imaging. 187-196 - Zheng Zhang, Zechen Zhou, Lei Xiang, Kelei He, Zhiqing Zhu, Xingang Wang, Zhiming Zeng, Hongqin Liang, Chen Liu:
7T-Like T1-Weighted and TOF MRI Synthesis from 3T MRI with Multi-contrast Complementary Deep Learning. 197-207 - Xin Zhu, Hongyi Pan, Batuhan Gundogdu, Debesh Jha, Yury Velichko, Adam B. Murphy, Ashley Ross, Baris Turkbey, Ahmet Enis Çetin, Ulas Bagci:
A Probabilistic Hadamard U-Net for MRI Bias Field Correction. 208-217 - Haoshen Wang, Xiaodong Wang, Zhiming Cui:
Structure-Preserving Diffusion Model for Unpaired Medical Image Translation. 218-227 - Georgia Kanli, Daniele Perlo, Selma Boudissa, Radovan Jirík, Olivier Keunen:
Simultaneous Image Quality Improvement and Artefacts Correction in Accelerated MRI. 228-237 - Boyuan Tan, Yuxin Xue, Lei Bi, Jinman Kim:
Full-TrSUN: A Full-Resolution Transformer UNet for High Quality PET Image Synthesis. 238-247 - Zejun Wu, Samuel W. Remedios, Blake E. Dewey, Aaron Carass, Jerry L. Prince:
TS-SR3: Time-Strided Denoising Diffusion Probabilistic Model for MR Super-Resolution. 248-258 - Bo Zhou, Tianqi Chen, Jun Hou, Yinchi Zhou, Huidong Xie, Chi Liu, James S. Duncan:
PDM: A Plug-and-Play Perturbed Multi-path Diffusion Module for Simultaneous Medical Image Segmentation Improvement and Uncertainty Estimation. 259-268 - Yihang Fu, Ziyang Chen, Yiwen Ye, Yong Xia:
DyNo: Dynamic Normalization based Test-Time Adaptation for 2D Medical Image Segmentation. 269-279 - Shoujun Yu, Cheng Li, Yousuf Babiker M. Osman, Shanshan Wang, Hairong Zheng:
Accurate Delineation of Cerebrovascular Structures from TOF-MRA with Connectivity-Reinforced Deep Learning. 280-289 - Long Chen, Dorit Merhof:
Learning Instance-Discriminative Pixel Embeddings Using Pixel Triplets. 290-299 - Yiming Chen, Niharika Shimona D'Souza, Akshith Mandepally, Patrick Henninger, Satyananda Kashyap, Neerav Karani, Neel Dey, Marcos Zachary, Raed Rizq, Paul Chouinard, Polina Golland, Tanveer F. Syeda-Mahmood:
Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound. 300-309 - Erik Gösche, Reza Eghbali, Florian Knoll, Andreas M. Rauschecker:
Domain Influence in MRI Medical Image Segmentation: Spatial Versus k-Space Inputs. 310-319 - Abdullah F. Al-Battal, Van Ha Tang, Steven Q. H. Truong, Truong Q. Nguyen, Cheolhong An:
Enhanced Small Liver Lesion Detection and Segmentation Using a Size-Focused Multi-model Approach in CT Scans. 320-330 - Arnau Farré-Melero, Pablo Aguiar-Fernández, Aida Niñerola-Baizán:
Generation and Segmentation of Simulated Total-Body PET Images. 331-339 - Yichen Yang, Pengbo Jiang, Xiran Cai, Zhong Xue, Dinggang Shen:
Integrating Convolutional Neural Network and Transformer for Lumen Prediction Along the Aorta Sections. 340-349 - Qiuting Hu, Li Lin, Pujin Cheng, Xiaoying Tang:
CSSD: Cross-Supervision and Self-denoising for Hybrid-Supervised Hepatic Vessel Segmentation. 350-360 - Mahdi Gilany, Mohamed Harmanani, Paul F. R. Wilson, Minh Nguyen Nhat To, Amoon Jamzad, Fahimeh Fooladgar, Brian Wodlinger, Purang Abolmaesumi, Parvin Mousavi:
Calibrated Diverse Ensemble Entropy Minimization for Robust Test-Time Adaptation in Prostate Cancer Detection. 361-371 - R. Neeraja, S. Devadharshiniinst, Venkateswaran N, Vivek Maik, Aparna Purayath, Manojkumar Lakshmanan, Mohanasankar Sivaprakasam:
SpineStyle: Conceptualizing Style Transfer for Image-Guided Spine Surgery on Radiographs. 372-381 - Shaoming Zheng, Yinsong Wang, Siyi Du, Chen Qin:
SGSR: Structure-Guided Multi-contrast MRI Super-Resolution via Spatio-Frequency Co-Query Attention. 382-391 - Weiheng Fu, Meilan Xu, Jie Wu, Xiaoshuang Shi, Kang Li, Xiaofeng Zhu:
Knowledge Distillation Based Dual-Branch Network for Whole Slide Image Analysis. 392-401 - Jiameng Liu, Furkan Pala, Islem Rekik, Dinggang Shen:
DHSampling: Diversity-Based Hyperedge Sampling in GNN Learning with Application to Medical Imaging Classification. 402-411
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