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ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: Vancouver, BC, Canada
- M. Emre Celebi
, Md Sirajus Salekin, Hyunwoo J. Kim
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops - ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings. Lecture Notes in Computer Science 14393, Springer 2023, ISBN 978-3-031-47400-2
Proceedings of the Eighth International Skin Imaging Collaboration Workshop (ISIC 2023)
- Nourhan Bayasi
Continual-GEN: Continual Group Ensembling for Domain-agnostic Skin Lesion Classification. 3-13 - Yuchen Tian, Jiacheng Wang, Yueming Jin, Liansheng Wang:
Communication-Efficient Federated Skin Lesion Classification with Generalizable Dataset Distillation. 14-24 - Siyi Du
AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets. 25-36 - Alceu Bissoto, Catarina Barata, Eduardo Valle, Sandra Avila:
Test-Time Selection for Robust Skin Lesion Analysis. 37-46 - Carlos Santiago, Miguel Correia, Maria Rita Verdelho, Alceu Bissoto, Catarina Barata:
Global and Local Explanations for Skin Cancer Diagnosis Using Prototypes. 47-56 - Naren Akash R. J, Anirudh Kaushik, Jayanthi Sivaswamy:
Evidence-Driven Differential Diagnosis of Malignant Melanoma. 57-66
Proceedings of the First Clinically-Oriented and Responsible AI for Medical Data Analysis (Care-AI 2023) Workshop
- Wenjie Kang, Bo Li, Janne M. Papma, Lize C. Jiskoot, Peter Paul De Deyn, Geert Jan Biessels, Jurgen A. H. R. Claassen, Huub A. M. Middelkoop, Wiesje M. van der Flier, Inez H. G. B. Ramakers, Stefan Klein, Esther E. Bron:
An Interpretable Machine Learning Model with Deep Learning-Based Imaging Biomarkers for Diagnosis of Alzheimer's Disease. 69-78 - Wen Tang, Chenhao Pei, Pengxin Yu, Huan Zhang, Xiangde Min, Cancan Chen, Han Kang, Weixin Xu, Rongguo Zhang:
Generating Chinese Radiology Reports from X-Ray Images: A Public Dataset and an X-ray-to-Reports Generation Method. 79-88 - David Bani-Harouni, Tamara T. Mueller, Daniel Rueckert, Georgios Kaissis:
Gradient Self-alignment in Private Deep Learning. 89-97 - Qiangqiang Gu, Nazim Shaikh, Ping-chang Lin, Srinath Jayachandran, Prasanna Porwal, Xiao Li, Yao Nie:
Cellular Features Based Interpretable Network for Classifying Cell-Of-Origin from Whole Slide Images for Diffuse Large B-cell Lymphoma Patients. 98-106 - Sara Ketabi, Pranav Agnihotri, Hamed Zakeri, Khashayar Namdar, Farzad Khalvati:
Multimodal Learning for Improving Performance and Explainability of Chest X-Ray Classification. 107-116
Proceedings of the First International Workshop on Foundation Models for Medical Artificial General Intelligence (MedAGI 2023)
- Sangwook Kim
Cross-Task Attention Network: Improving Multi-task Learning for Medical Imaging Applications. 119-128 - Yizhe Zhang, Tao Zhou, Shuo Wang, Peixian Liang, Yejia Zhang, Danny Z. Chen:
Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model. 129-139 - Heejong Kim, Victor Ion Butoi, Adrian V. Dalca, Mert R. Sabuncu:
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging. 140-150 - Yizhe Zhang, Danny Z. Chen:
GPT4MIA: Utilizing Generative Pre-trained Transformer (GPT-3) as a Plug-and-Play Transductive Model for Medical Image Analysis. 151-160 - Jingwei Zhang
SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology. 161-170 - Fuping Wu, Le Zhang, Yang Sun, Yuanhan Mo, Thomas E. Nichols, Bartlomiej W. Papiez:
Multi-task Cooperative Learning via Searching for Flat Minima. 171-181 - Dewei Hu, Hao Li, Han Liu, Xing Yao, Jiacheng Wang, Ipek Oguz:
MAP: Domain Generalization via Meta-Learning on Anatomy-Consistent Pseudo-Modalities. 182-192 - Qingyang Wu
A General Computationally-Efficient 3D Reconstruction Pipeline for Multiple Images with Point Clouds. 193-202 - Anh Tien Nguyen, Jin Tae Kwak:
GPC: Generative and General Pathology Image Classifier. 203-212 - Julio Silva-Rodríguez, Jose Dolz, Ismail Ben Ayed:
Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ Segmentation. 213-224 - Injae Kim, Jongha Kim, Joonmyung Choi, Hyunwoo J. Kim:
Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification. 225-233 - An Wang, Mobarakol Islam, Mengya Xu, Yang Zhang, Hongliang Ren:
SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation. 234-244 - Seungkyu Kim, Hyun-Jic Oh, Seonghui Min
Evaluation and Improvement of Segment Anything Model for Interactive Histopathology Image Segmentation. 245-255 - Rachana Sathish, Rahul Venkataramani, K. S. Shriram, Prasad Sudhakar:
Task-Driven Prompt Evolution for Foundation Models. 256-264 - Sharon Chokuwa
Generalizing Across Domains in Diabetic Retinopathy via Variational Autoencoders. 265-274 - Dongik Shin, Beomsuk Kim, Seungjun Baek:
CEmb-SAM: Segment Anything Model with Condition Embedding for Joint Learning from Heterogeneous Datasets. 275-284 - Vaibhav Khamankar, Sutanu Bera, Saumik Bhattacharya, Debashis Sen, Prabir Kumar Biswas:
Histopathological Image Analysis with Style-Augmented Feature Domain Mixing for Improved Generalization. 285-294
Proceedings of the Fourth Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2023)
- Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter J. Schüffler, Nassir Navab:
DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks. 297-310 - Pochuan Wang, Chen Shen, Weichung Wang, Masahiro Oda
ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated Data. 311-321 - Yann Fraboni, Lucia Innocenti, Michela Antonelli, Richard Vidal, Laetitia Kameni, Sébastien Ourselin, Marco Lorenzi:
Validation of Federated Unlearning on Collaborative Prostate Segmentation. 322-333 - Marawan Elbatel
Federated Model Aggregation via Self-supervised Priors for Highly Imbalanced Medical Image Classification. 334-346 - Ruoyou Wu, Cheng Li, Juan Zou, Shanshan Wang:
FedAutoMRI: Federated Neural Architecture Search for MR Image Reconstruction. 347-356 - Geng Zhan, Jiajun Deng, Mariano Cabezas
Fed-CoT: Co-teachers for Federated Semi-supervised MS Lesion Segmentation. 357-366 - Chamani Shiranthika
SplitFed Resilience to Packet Loss: Where to Split, that is the Question. 367-377
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