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ORCID26th MICCAI 2023: Vancouver, BC, Canada - Part II
- Hayit Greenspan, Anant Madabhushi
, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part II. Lecture Notes in Computer Science 14221, Springer 2023, ISBN 978-3-031-43894-3
Machine Learning - Learning Strategies
- Linhao Qu, Yingfan Ma, Zhiwei Yang, Manning Wang, Zhijian Song:
OpenAL: An Efficient Deep Active Learning Framework for Open-Set Pathology Image Classification. 3-13 - Fan Bai, Ke Yan, Xiaoyu Bai, Xinyu Mao, Xiaoli Yin, Jingren Zhou, Yu Shi, Le Lu, Max Q.-H. Meng:
SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation. 14-24 - Han Liu, Hao Li, Xing Yao, Yubo Fan, Dewei Hu, Benoit M. Dawant, Vishwesh Nath, Zhoubing Xu, Ipek Oguz:
COLosSAL: A Benchmark for Cold-Start Active Learning for 3D Medical Image Segmentation. 25-34 - Yixiao Zhang, Xinyi Li, Huimiao Chen, Alan L. Yuille, Yaoyao Liu, Zongwei Zhou:
Continual Learning for Abdominal Multi-organ and Tumor Segmentation. 35-45 - Xiaofeng Liu, Helen A. Shih, Fangxu Xing, Emiliano Santarnecchi, Georges El Fakhri, Jonghye Woo:
Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI. 46-56 - Yucheng Tang, Yipeng Hu, Jing Li, Hu Lin, Xiang Xu, Ke Huang, Hongxiang Lin:
PLD-AL: Pseudo-label Divergence-Based Active Learning in Carotid Intima-Media Segmentation for Ultrasound Images. 57-67 - Wentao Zhang, Yujun Huang, Tong Zhang, Qingsong Zou, Wei-Shi Zheng, Ruixuan Wang:
Adapter Learning in Pretrained Feature Extractor for Continual Learning of Diseases. 68-78 - Md Abdul Kadir, Hasan Md Tusfiqur Alam, Daniel Sonntag:
EdgeAL: An Edge Estimation Based Active Learning Approach for OCT Segmentation. 79-89 - Jingna Qiu, Frauke Wilm, Mathias Öttl, Maja Schlereth, Chang Liu, Tobias Heimann, Marc Aubreville, Katharina Breininger:
Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation. 90-100 - Kihyun You, Jawook Gu, Jiyeon Ham, Beomhee Park, Jiho Kim, Eun Kyoung Hong, Woonhyuk Baek, Byungseok Roh:
CXR-CLIP: Toward Large Scale Chest X-ray Language-Image Pre-training. 101-111 - Mohammad Mozafari, Adeleh Bitarafan, Mohammad Farid Azampour, Azade Farshad, Mahdieh Soleymani Baghshah, Nassir Navab:
VISA-FSS: A Volume-Informed Self Supervised Approach for Few-Shot 3D Segmentation. 112-122 - Kaushik Roy, Peyman Moghadam, Mehrtash Harandi:
L3DMC: Lifelong Learning Using Distillation via Mixed-Curvature Space. 123-133
Machine Learning - Explainability, Bias, and Uncertainty I
- Meng Zhou, Zhe Xu, Kang Zhou, Raymond Kai-Yu Tong:
Weakly Supervised Medical Image Segmentation via Superpixel-Guided Scribble Walking and Class-Wise Contrastive Regularization. 137-147 - Yuhan Zhang, Kun Huang, Cheng Chen, Qiang Chen, Pheng-Ann Heng:
SATTA: Semantic-Aware Test-Time Adaptation for Cross-Domain Medical Image Segmentation. 148-158 - Zecheng Liu, Jia Wei, Rui Li, Jianlong Zhou:
SFusion: Self-attention Based N-to-One Multimodal Fusion Block. 159-169 - Zhifang Deng, Dandan Li, Shi Tan, Ying Fu, Xueguang Yuan, Xiaohong Huang, Yong Zhang, Guangwei Zhou:
FedGrav: An Adaptive Federated Aggregation Algorithm for Multi-institutional Medical Image Segmentation. 170-180 - Yiming Qian, Liangzhi Li, Huazhu Fu, Meng Wang, Qingsheng Peng, Yih Chung Tham, Ching Yu Cheng, Yong Liu, Rick Siow Mong Goh, Xinxing Xu:
Category-Independent Visual Explanation for Medical Deep Network Understanding. 181-191 - Zhenxi Zhang, Ran Ran, Chunna Tian, Heng Zhou, Xin Li, Fan Yang, Zhicheng Jiao:
Self-aware and Cross-Sample Prototypical Learning for Semi-supervised Medical Image Segmentation. 192-201 - Chenyu Xue, Fan Wang, Yuanzhuo Zhu, Hui Li, Deyu Meng, Dinggang Shen, Chunfeng Lian:
NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical Development Patterns of Preterm Infants. 202-211 - Jaeung Lee, Keunho Byeon, Jin Tae Kwak:
Centroid-Aware Feature Recalibration for Cancer Grading in Pathology Images. 212-221 - Meng Wang, Lianyu Wang, Xinxing Xu, Ke Zou, Yiming Qian, Rick Siow Mong Goh, Yong Liu, Huazhu Fu:
Federated Uncertainty-Aware Aggregation for Fundus Diabetic Retinopathy Staging. 222-232 - Yi Lin, Yufan Chen, Kwang-Ting Cheng, Hao Chen:
Few Shot Medical Image Segmentation with Cross Attention Transformer. 233-243 - Yilan Zhang, Jianqi Chen, Ke Wang, Fengying Xie:
ECL: Class-Enhancement Contrastive Learning for Long-Tailed Skin Lesion Classification. 244-254 - Nilesh Kumar, Prashnna K. Gyawali, Sandesh Ghimire, Linwei Wang:
Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation. 255-265 - Linrui Dai, Wenhui Lei, Xiaofan Zhang:
Efficient Subclass Segmentation in Medical Images. 266-275 - Dwarikanath Mahapatra, Antonio José Jimeno-Yepes, Shiba Kuanar, Sudipta Roy, Behzad Bozorgtabar, Mauricio Reyes, Zongyuan Ge:
Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification. 276-286 - Jiaxing Gao, Lin Zhao, Tianyang Zhong, Changhe Li, Zhibin He, Yaonai Wei, Shu Zhang, Lei Guo, Tianming Liu, Junwei Han, Tuo Zhang:
Prediction of Cognitive Scores by Joint Use of Movie-Watching fMRI Connectivity and Eye Tracking via Attention-CensNet. 287-296 - Zheng Zhang, Xiaolei Zhang, Yaolei Qi, Guanyu Yang:
Partial Vessels Annotation-Based Coronary Artery Segmentation with Self-training and Prototype Learning. 297-306 - Zikang Xu, Shang Zhao, Quan Quan, Qingsong Yao, S. Kevin Zhou:
FairAdaBN: Mitigating Unfairness with Adaptive Batch Normalization and Its Application to Dermatological Disease Classification. 307-317 - Minghui Chen, Meirui Jiang, Qi Dou, Zehua Wang, Xiaoxiao Li:
FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation. 318-328 - Xierui Wang, Hanning Ying, Xiaoyin Xu, Xiujun Cai, Min Zhang:
TransLiver: A Hybrid Transformer Model for Multi-phase Liver Lesion Classification. 329-338 - Yuhao Du, Yuncheng Jiang, Shuangyi Tan, Xusheng Wu, Qi Dou, Zhen Li, Guanbin Li, Xiang Wan:
ArSDM: Colonoscopy Images Synthesis with Adaptive Refinement Semantic Diffusion Models. 339-349 - Faris Almalik, Naif Alkhunaizi, Ibrahim Almakky, Karthik Nandakumar:
FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling. 350-360 - Sergio Tascon-Morales, Pablo Márquez-Neila, Raphael Sznitman:
Localized Questions in Medical Visual Question Answering. 361-370 - Yoni Choukroun, Lior Golgher, Pablo Blinder, Lior Wolf:
Reconstructing the Hemodynamic Response Function via a Bimodal Transformer. 371-381 - Chenlu Zhan, Peng Peng, Hanrong Zhang, Haiyue Sun, Chunnan Shang, Tao Chen, Hongsen Wang, Gaoang Wang, Hongwei Wang:
Debiasing Medical Visual Question Answering via Counterfactual Training. 382-393 - Defu Yang, Hui Shen, Minghan Chen, Yitian Xue, Shuai Wang, Guorong Wu, Wentao Zhu:
Spatiotemporal Hub Identification in Brain Network by Learning Dynamic Graph Embedding on Grassmannian Manifold. 394-402 - Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Mototaka Miyake, Yasuyuki Takamizawa, Sono Ito, Hirokazu Watanabe, Yukihiro Yoshida, Hiroki Yoshimura, Tatsuya Harada, Ryuji Hamamoto:
Towards AI-Driven Radiology Education: A Self-supervised Segmentation-Based Framework for High-Precision Medical Image Editing. 403-413 - Pramit Saha, Divyanshu Mishra, J. Alison Noble:
Rethinking Semi-Supervised Federated Learning: How to Co-train Fully-Labeled and Fully-Unlabeled Client Imaging Data. 414-424 - Susu Sun, Lisa M. Koch, Christian F. Baumgartner:
Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations? 425-434 - Luisa Gallée, Meinrad Beer, Michael Götz:
Interpretable Medical Image Classification Using Prototype Learning and Privileged Information. 435-445 - Juyeon Heo, Pingfan Song, Weiyang Liu, Adrian Weller:
Physics-Based Decoding Improves Magnetic Resonance Fingerprinting. 446-456 - Asif Hanif, Muzammal Naseer, Salman H. Khan, Mubarak Shah, Fahad Shahbaz Khan:
Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation. 457-467 - Xiangyi Yan, Junayed Naushad, Chenyu You, Hao Tang, Shanlin Sun, Kun Han, Haoyu Ma, James S. Duncan, Xiaohui Xie:
Localized Region Contrast for Enhancing Self-supervised Learning in Medical Image Segmentation. 468-478 - Chao Qin, Jiale Cao, Huazhu Fu, Rao Muhammad Anwer, Fahad Shahbaz Khan:
A Spatial-Temporal Deformable Attention Based Framework for Breast Lesion Detection in Videos. 479-488 - Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert:
A Flexible Framework for Simulating and Evaluating Biases in Deep Learning-Based Medical Image Analysis. 489-499 - Meirui Jiang, Yuan Zhong, Anjie Le, Xiaoxiao Li, Qi Dou:
Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging. 500-510 - Xinrui Zhou, Yuhao Huang, Wufeng Xue, Xin Yang, Yuxin Zou, Qilong Ying, Yuanji Zhang, Jia Liu, Jie Ren, Dong Ni:
Inflated 3D Convolution-Transformer for Weakly-Supervised Carotid Stenosis Grading with Ultrasound Videos. 511-520 - Myeongkyun Kang, Philip Chikontwe, Soopil Kim, Kyong Hwan Jin, Ehsan Adeli-Mosabbeb, Kilian M. Pohl, Sanghyun Park:
One-Shot Federated Learning on Medical Data Using Knowledge Distillation with Image Synthesis and Client Model Adaptation. 521-531 - Marcel Beetz, Abhirup Banerjee, Vicente Grau:
Multi-objective Point Cloud Autoencoders for Explainable Myocardial Infarction Prediction. 532-542 - Youssef Assis, Liang Liao, Fabien Pierre, René Anxionnat, Erwan Kerrien:
Aneurysm Pose Estimation with Deep Learning. 543-553 - Viktor van der Valk, Douwe Atsma, Roderick Scherptong, Marius Staring:
Joint Optimization of a β-VAE for ECG Task-Specific Feature Extraction. 554-563 - Muhammad Asad, Helena Williams, Indrajeet Mandal, Sarim Ather, Jan Deprest, Jan D'hooge, Tom Vercauteren:
Adaptive Multi-scale Online Likelihood Network for AI-Assisted Interactive Segmentation. 564-574 - Alfie Roddan, Chi Xu, Serine Ajlouni, Irini Kakaletri, Patra Charalampaki, Stamatia Giannarou:
Explainable Image Classification with Improved Trustworthiness for Tissue Characterisation. 575-585 - Shaotong Zhu, Michael Wan, Elaheh Hatamimajoumerd, Kashish Jain, Samuel Zlota, Cholpady Vikram Kamath, Cassandra B. Rowan, Emma C. Grace, Matthew S. Goodwin, Marie J. Hayes, Rebecca A. Schwartz-Mette, Emily Zimmerman, Sarah Ostadabbas:
A Video-Based End-to-end Pipeline for Non-nutritive Sucking Action Recognition and Segmentation in Young Infants. 586-595 - Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin:
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. 596-606 - Thomas Pinetz, Erich Kobler, Robert Haase, Katerina Deike-Hofmann, Alexander Radbruch, Alexander Effland:
Faithful Synthesis of Low-Dose Contrast-Enhanced Brain MRI Scans Using Noise-Preserving Conditional GANs. 607-617 - Jiale Cheng, Xin Zhang, Fenqiang Zhao, Zhengwang Wu, Xinrui Yuan, Li Wang, Weili Lin, Gang Li:
Prediction of Infant Cognitive Development with Cortical Surface-Based Multimodal Learning. 618-627 - Shantanu Ghosh, Ke Yu, Kayhan Batmanghelich:
Distilling BlackBox to Interpretable Models for Efficient Transfer Learning. 628-638 - Amine Amyar, Shiro Nakamori, Manuel Morales, Siyeop Yoon, Jennifer Rodriguez, Jiwon Kim, Robert M. Judd, Jonathan W. Weinsaft, Reza Nezafat:
Gadolinium-Free Cardiac MRI Myocardial Scar Detection by 4D Convolution Factorization. 639-648 - Thomas Z. Li, John M. Still, Kaiwen Xu, Ho Hin Lee, Leon Y. Cai, Aravind R. Krishnan, Riqiang Gao, Mirza S. Khan, Sanja Antic, Michael N. Kammer, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman, Thomas A. Lasko:
Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures from Routine EHRs for Pulmonary Nodule Classification. 649-659 - Qin Zhou, Guoyan Zheng:
FedContrast-GPA: Heterogeneous Federated Optimization via Local Contrastive Learning and Global Process-Aware Aggregation. 660-670 - Qin Zhou, Peng Liu, Guoyan Zheng:
Partially Supervised Multi-organ Segmentation via Affinity-Aware Consistency Learning and Cross Site Feature Alignment. 671-680 - Rong Zhou, Houliang Zhou, Brian Y. Chen, Li Shen, Yu Zhang, Lifang He:
Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer's Disease Using Multimodal Imaging Genetics. 681-691 - Nannan Wu, Li Yu, Xin Yang, Kwang-Ting Cheng, Zengqiang Yan:
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification. 692-702 - Chen Yang, Yifan Liu, Yixuan Yuan:
Transferability-Guided Multi-source Model Adaptation for Medical Image Segmentation. 703-712 - Ze Jin, Maolin Pang, Yuqiao Yang, Fahad Parvez Mahdi, Tianyi Qu, Ren Sasage, Kenji Suzuki:
Explaining Massive-Training Artificial Neural Networks in Medical Image Analysis Task Through Visualizing Functions Within the Models. 713-722 - Favour Nerrise, Qingyu Zhao, Kathleen L. Poston, Kilian M. Pohl, Ehsan Adeli:
An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment. 723-733 - Nina Weng, Martyna Plomecka, Manuel Kaufmann, Ard Kastrati, Roger Wattenhofer, Nicolas Langer:
An Interpretable and Attention-Based Method for Gaze Estimation Using Electroencephalography. 734-743 - D. Hudson Smith, John Paul Lineberger, George H. Baker:
On the Relevance of Temporal Features for Medical Ultrasound Video Recognition. 744-753 - Jiarong Ye, Haomiao Ni, Peng Jin, Sharon X. Huang, Yuan Xue:
Synthetic Augmentation with Large-Scale Unconditional Pre-training. 754-764 - Hang Zhang, Rongguang Wang, Renjiu Hu, Jinwei Zhang, Jiahao Li:
DeDA: Deep Directed Accumulator. 765-775 - Hyuna Cho, Guorong Wu, Won Hwa Kim:
Mixing Temporal Graphs with MLP for Longitudinal Brain Connectome Analysis. 776-786
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