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ORCID27th MICCAI 2024: Marrakesh, Morocco - Part X
- Marius George Linguraru
, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part X. Lecture Notes in Computer Science 15010, Springer 2024, ISBN 978-3-031-72116-8
Machine Learning - Generalizability/Explainability/Fairness/Uncertainty
- Emir Konuk, Robert Welch, Filip Christiansen, Elisabeth Epstein, Kevin Smith:
A Framework for Assessing Joint Human-AI Systems Based on Uncertainty Estimation. 3-12 - Yunlu Yan, Lei Zhu, Yuexiang Li, Xinxing Xu, Rick Siow Mong Goh, Yong Liu, Salman H. Khan, Chun-Mei Feng:
A New Perspective to Boost Performance Fairness For Medical Federated Learning. 13-23 - Qingpeng Kong, Ching-Hao Chiu, Dewen Zeng, Yu-Jen Chen, Tsung-Yi Ho, Jingtong Hu, Yiyu Shi:
Achieving Fairness Through Channel Pruning for Dermatological Disease Diagnosis. 24-34 - Townim F. Chowdhury, Vu Minh Hieu Phan, Kewen Liao, Minh-Son To, Yutong Xie, Anton van den Hengel, Johan W. Verjans, Zhibin Liao:
AdaCBM: An Adaptive Concept Bottleneck Model for Explainable and Accurate Diagnosis. 35-45 - Yunhe Gao, Difei Gu, Mu Zhou, Dimitris N. Metaxas:
Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification. 46-56 - Xiao Fang, Yi Lin, Dong Zhang, Kwang-Ting Cheng, Hao Chen:
Aligning Medical Images with General Knowledge from Large Language Models. 57-67 - Mikhail Goncharov, Valentin Samokhin, Eugenia Soboleva, Roman Sokolov, Boris Shirokikh, Mikhail Belyaev, Anvar Kurmukov, Ivan Oseledets:
Anatomical Positional Embeddings. 68-77 - Ji-Hun Oh, Kianoush Falahkheirkhah, Rohit Bhargava:
Are We Ready for Out-of-Distribution Detection in Digital Pathology? 78-89 - Nourhan Bayasi, Jamil Fayyad, Alceu Bissoto, Ghassan Hamarneh, Rafeef Garbi:
BiasPruner: Debiased Continual Learning for Medical Image Classification. 90-101 - Pranav Poudel, Prashant Shrestha, Sanskar Amgain, Yash Raj Shrestha, Prashnna K. Gyawali, Binod Bhattarai:
CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities. 102-112 - Junlin Hou, Jilan Xu, Hao Chen:
Concept-Attention Whitening for Interpretable Skin Lesion Diagnosis. 113-123 - Evangelia Christodoulou, Annika Reinke, Rola Houhou, Piotr Kalinowski, Selen Erkan, Carole H. Sudre, Ninon Burgos, Sofiène Boutaj, Sophie Loizillon, Maëlys Solal, Nicola Rieke, Veronika Cheplygina, Michela Antonelli, Leon D. Mayer, Minu Dietlinde Tizabi, M. Jorge Cardoso, Amber Simpson, Paul F. Jäger, Annette Kopp-Schneider, Gaël Varoquaux, Olivier Colliot, Lena Maier-Hein:
Confidence Intervals Uncovered: Are We Ready for Real-World Medical Imaging AI? 124-132 - Saurabh Sharma, Atul Kumar, Joydeep Chandra:
Confidence Matters: Enhancing Medical Image Classification Through Uncertainty-Driven Contrastive Self-distillation. 133-142 - Shiyu Liu, Fan Wang, Zehua Ren, Chunfeng Lian, Jianhua Ma:
Controllable Counterfactual Generation for Interpretable Medical Image Classification. 143-152 - Yi Sheng, Junhuan Yang, Jinyang Li, James Alaina, Xiaowei Xu, Yiyu Shi, Jingtong Hu, Weiwen Jiang, Lei Yang:
Data-Algorithm-Architecture Co-Optimization for Fair Neural Networks on Skin Lesion Dataset. 153-163 - Ruinan Jin, Wenlong Deng, Minghui Chen, Xiaoxiao Li:
Debiased Noise Editing on Foundation Models for Fair Medical Image Classification. 164-174 - Yuanhang Zheng, Yiqiao Qiu, Haoxuan Che, Hao Chen, Wei-Shi Zheng, Ruixuan Wang:
Deep Model Reference: Simple Yet Effective Confidence Estimation for Image Classification. 175-185 - Roshan Prakash Rane, JiHoon Kim, Arjun Umesha, Didem Stark, Marc-André Schulz, Kerstin Ritter:
DeepRepViz: Identifying Potential Confounders in Deep Learning Model Predictions. 186-196 - Jianan Chen, Vishwesh Ramanathan, Tony Xu, Anne L. Martel:
Detecting Noisy Labels with Repeated Cross-Validations. 197-207 - Yingying Fang, Shuang Wu, Zihao Jin, Shiyi Wang, Caiwen Xu, Simon Walsh, Guang Yang:
DiffExplainer: Unveiling Black Box Models Via Counterfactual Generation. 208-218 - Gurur Gamgam, Alkan Kabakçioglu, Demet Yüksel Dal, Burak Acar:
Disentangled Attention Graph Neural Network for Alzheimer's Disease Diagnosis. 219-228 - Jing Du, Guangwei Dong, Congbo Ma, Shan Xue, Jia Wu, Jian Yang, Amin Beheshti, Quan Z. Sheng, Alexis Giral:
Distributionally-Adaptive Variational Meta Learning for Brain Graph Classification. 229-239 - Zhipeng Deng, Luyang Luo, Hao Chen:
Enable the Right to be Forgotten with Federated Client Unlearning in Medical Imaging. 240-250 - Ruijie Yang, Yan Zhu, Peiyao Fu, Yizhe Zhang, Zhihua Wang, Quanlin Li, Pinghong Zhou, Xian Yang, Shuo Wang:
EndoFinder: Online Image Retrieval for Explainable Colorectal Polyp Diagnosis. 251-262 - Yuexuan Xia, Benteng Ma, Qi Dou, Yong Xia:
Enhancing Federated Learning Performance Fairness via Collaboration Graph-Based Reinforcement Learning. 263-272 - Rachaell Nihalaani, Tushar Kataria, Jadie Adams, Shireen Y. Elhabian:
Estimation and Analysis of Slice Propagation Uncertainty in 3D Anatomy Segmentation. 273-285 - Kaouther Mouheb, Marawan Elbatel, Stefan Klein, Esther E. Bron:
Evaluating the Fairness of Neural Collapse in Medical Image Classification. 286-296 - Jiaqi Wu, Wei Peng, Binxu Li, Yu Zhang, Kilian M. Pohl:
Evaluating the Quality of Brain MRI Generators. 297-307 - Yibo Gao, Zheyao Gao, Xin Gao, Yuanye Liu, Bomin Wang, Xiahai Zhuang:
Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis. 308-317 - Victor Wåhlstrand Skärström, Lisa Johansson, Jennifer Alvén, Mattias Lorentzon, Ida Häggström:
Explainable Vertebral Fracture Analysis with Uncertainty Estimation Using Differentiable Rule-Based Classification. 318-328 - Yuanbo Guo, Zhenge Jia, Jingtong Hu, Yiyu Shi:
FairQuantize: Achieving Fairness Through Weight Quantization for Dermatological Disease Diagnosis. 329-338 - Giorgio Roffo, Carlo Biffi, Pietro Salvagnini, Andrea Cherubini:
Feature Selection Gates with Gradient Routing for Endoscopic Image Computing. 339-349 - Francesco Galati, Rosa Cortese, Ferran Prados, Marco Lorenzi, Maria A. Zuluaga:
Federated Multi-centric Image Segmentation with Uneven Label Distribution. 350-360 - Jiayi Chen, Benteng Ma, Hengfei Cui, Yong Xia:
FedEvi: Improving Federated Medical Image Segmentation via Evidential Weight Aggregation. 361-372 - Yangyang Xiang, Nannan Wu, Li Yu, Xin Yang, Kwang-Ting Cheng, Zengqiang Yan:
FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation Completeness. 373-382 - Kumail Alhamoud, Yasir Ghunaim, Motasem Alfarra, Thomas Hartvigsen, Philip Torr, Bernard Ghanem, Adel Bibi, Marzyeh Ghassemi:
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging. 383-393 - Zhaobin Sun, Nannan Wu, Junjie Shi, Li Yu, Kwang-Ting Cheng, Zengqiang Yan:
FedMLP: Federated Multi-label Medical Image Classification Under Task Heterogeneity. 394-404 - Malte Tölle, Fernando Navarro, Sebastian Eble, Ivo Wolf, Bjoern H. Menze, Sandy Engelhardt:
FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels. 405-415 - Xiongri Shen, Zhenxi Song, Zhiguo Zhang:
GCAN: Generative Counterfactual Attention-Guided Network for Explainable Cognitive Decline Diagnostics Based on fMRI Functional Connectivity. 416-426 - Peng Xia, Ming Hu, Feilong Tang, Wenxue Li, Wenhao Zheng, Lie Ju, Peibo Duan, Huaxiu Yao, Zongyuan Ge:
Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations. 427-437 - Jingjun Yi, Qi Bi, Hao Zheng, Haolan Zhan, Wei Ji, Yawen Huang, Shaoxin Li, Yuexiang Li, Yefeng Zheng, Feiyue Huang:
Hallucinated Style Distillation for Single Domain Generalization in Medical Image Segmentation. 438-448 - Matthew Tivnan, Siyeop Yoon, Zhennong Chen, Xiang Li, Dufan Wu, Quanzheng Li:
Hallucination Index: An Image Quality Metric for Generative Reconstruction Models. 449-458 - Zhe Li, Bernhard Kainz:
Image Distillation for Safe Data Sharing in Histopathology. 459-469 - Jing Xia, Yi Hao Chan, Deepank Girish, Jagath C. Rajapakse:
IMG-GCN: Interpretable Modularity-Guided Structure-Function Interactions Learning for Brain Cognition and Disorder Analysis. 470-480 - Mat De Vries, Reed Naidoo, Olga Fourkioti, Lucas G. Dent, Nathan Curry, Christopher Dunsby, Chris Bakal:
Interpretable Phenotypic Profiling of 3D Cellular Morphodynamics. 481-491 - Maxime Di Folco, Cosmin I. Bercea, Emily Chan, Julia A. Schnabel:
Interpretable Representation Learning of Cardiac MRI via Attribute Regularization. 492-501 - Julius Gervelmeyer, Sarah Müller, Kerol Djoumessi, David Merle, Simon J. Clark, Lisa M. Koch, Philipp Berens:
Interpretable-by-Design Deep Survival Analysis for Disease Progression Modeling. 502-512 - Abhishek Singh Sambyal, Usma Niyaz, Saksham Shrivastava, Narayanan C. Krishnan, Deepti R. Bathula:
LS+: Informed Label Smoothing for Improving Calibration in Medical Image Classification. 513-523 - Hyeon Bae Kim, Yong Hyun Ahn, Seong Tae Kim:
Mask-Free Neuron Concept Annotation for Interpreting Neural Networks in Medical Domain. 524-533 - Luyuan Xie, Manqing Lin, ChenMing Xu, Tianyu Luan, Zhipeng Zeng, Wenjun Qian, Cong Li, Yuejian Fang, Qingni Shen, Zhonghai Wu:
MH-pFLGB: Model Heterogeneous Personalized Federated Learning via Global Bypass for Medical Image Analysis. 534-545 - Tian Xia, Mélanie Roschewitz, Fabio De Sousa Ribeiro, Charles Jones, Ben Glocker:
Mitigating Attribute Amplification in Counterfactual Image Generation. 546-556 - Aobo Chen, Yangyi Li, Wei Qian, Kathy Morse, Chenglin Miao, Mengdi Huai:
Modeling and Understanding Uncertainty in Medical Image Classification. 557-567 - Laura Pfaff, Fabian Wagner, Nastassia Vysotskaya, Mareike Thies, Noah Maul, Siyuan Mei, Tobias Würfl, Andreas K. Maier:
No-New-Denoiser: A Critical Analysis of Diffusion Models for Medical Image Denoising. 568-578 - Qinghao Liang, Brendan Adkinson, Rongtao Jiang, Dustin Scheinost:
Overcoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling. 579-588 - Jiacheng Liu, Wenhua Qian, Jinde Cao, Peng Liu:
Overlay Mantle-Free for Semi-supervised Medical Image Segmentation. 589-598 - Luyuan Xie, Manqing Lin, Siyuan Liu, ChenMing Xu, Tianyu Luan, Cong Li, Yuejian Fang, Qingni Shen, Zhonghai Wu:
pFLFE: Cross-silo Personalized Federated Learning via Feature Enhancement on Medical Image Segmentation. 599-610 - Moo Hyun Son, Juyoung Bae, Elizabeth Tong, Hao Chen:
Progressive Knowledge Distillation for Automatic Perfusion Parameter Maps Generation from Low Temporal Resolution CT Perfusion Images. 611-621 - Hongye Zeng, Ke Zou, Zhihao Chen, Rui Zheng, Huazhu Fu:
Reliable Source Approximation: Source-Free Unsupervised Domain Adaptation for Vestibular Schwannoma MRI Segmentation. 622-632 - Benjamin Lambert, Florence Forbes, Senan Doyle, Michel Dojat:
Robust Conformal Volume Estimation in 3D Medical Images. 633-643 - Sebastian Doerrich, Francesco Di Salvo, Christian Ledig:
Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization. 644-654 - Xuyang Li, Weizhuo Zhang, Yue Yu, Wei-Shi Zheng, Tong Zhang, Ruixuan Wang:
SiFT: A Serial Framework with Textual Guidance for Federated Learning. 655-665 - Mazlum Ferhat Arslan, Weihong Guo, Shuo Li:
Single-source Domain Generalization in Deep Learning Segmentation via Lipschitz Regularization. 666-674 - Zeinab Abboud, Herve Lombaert, Samuel Kadoury:
Sparse Bayesian Networks: Efficient Uncertainty Quantification in Medical Image Analysis. 675-684 - Meilu Zhu, Qiushi Yang, Zhifan Gao, Jun Liu, Yixuan Yuan:
Stealing Knowledge from Pre-trained Language Models for Federated Classifier Debiasing. 685-695 - Paul Fischer, Hannah Willms, Moritz Schneider, Daniela Thorwarth, Michael Muehlebach, Christian F. Baumgartner:
Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy. 696-706 - Shuang Zeng, Pengxin Guo, Shuai Wang, Jianbo Wang, Yuyin Zhou, Liangqiong Qu:
Tackling Data Heterogeneity in Federated Learning via Loss Decomposition. 707-717 - Kerol Djoumessi, Bubacarr Bah, Laura Kühlewein, Philipp Berens, Lisa M. Koch:
This Actually Looks Like that: Proto-BagNets for Local and Global Interpretability-by-Design. 718-728 - Marvin Tom Teichmann, Manasi Datar, Lisa Kratzke, Fernando Vega, Florin C. Ghesu:
Towards Integrating Epistemic Uncertainty Estimation into the Radiotherapy Workflow. 729-738 - Zhicheng Dong, Xiaodong Yue, Yufei Chen, Xujing Zhou, Jiye Liang:
Uncertainty-Aware Multi-view Learning for Prostate Cancer Grading with DWI. 739-748 - Ali Ghadiri, Maurice Pagnucco, Yang Song:
XTranPrune: eXplainability-Aware Transformer Pruning for Bias Mitigation in Dermatological Disease Classification. 749-758
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