Medical Image Datasets

Medical image datasets are crucial for training and evaluating machine learning models used in disease diagnosis and treatment planning. Current research focuses on addressing challenges like data scarcity and imbalance through techniques such as data augmentation (including GANs and image translation), test-time training, and federated learning to improve model performance and generalization across diverse patient populations and imaging modalities. Convolutional neural networks (CNNs), transformers, and large multi-modal models are prominent architectures, often combined with techniques to enhance interpretability and mitigate biases. These advancements hold significant potential for improving the accuracy, efficiency, and accessibility of medical image analysis, ultimately leading to better patient care.

Papers

July 19, 2023

Class Attention to Regions of Lesion for Imbalanced Medical Image Recognition
Jia-Xin Zhuang, Jiabin Cai, Jianguo Zhang, Wei-shi Zheng, Ruixuan Wang
Medical Image Classification Medical Image Datasets Region Specific CNN Architecture True Class Imbalanced Medical Image Lesion Image

June 29, 2023

PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification
Tao Wang, Xinlin Zhang, Yuanbo Zhou, Junlin Lan, Tao Tan, Min Du, Qinquan Gao, Tong Tong
Classification Code Active Learning Medical Image Segmentation Medical Image Classification Medical Image Datasets PCa Detection Small Perturbation Based Active Learning

June 27, 2023

See Through the Fog: Curriculum Learning with Progressive Occlusion in Medical Imaging
Pradeep Singh, Kishore Babu Nampalle, Uppala Vivek Narayan, Balasubramanian Raman
Medical Image Medical Imaging Curriculum Learning Medical Image Datasets Partial Occlusion

June 26, 2023

Medical Federated Model with Mixture of Personalized and Sharing Components
Yawei Zhao, Qinghe Liu, Xinwang Liu, Kunlun He
Federated Learning Mixture Component Medical Image Datasets Medical Datasets Personalized Subject Medical Data Heterogeneous Clinical

June 24, 2023

Utilizing Segment Anything Model For Assessing Localization of GRAD-CAM in Medical Imaging
Evan Kellener, Ihina Nath, An Ngo, Thomas Nguyen, Joshua Schuman, Coen Adler, Arnav Kartikeya
Segment Anything Model Localization Focus Medical Imaging Saliency Map Human Annotation Medical Image Datasets Grad CAM

June 4, 2023

Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation
Yunhe Gao, Zhuowei Li, Di Liu, Mu Zhou, Shaoting Zhang, Dimitris N. Metaxas
Training Data Medical Image Segmentation Image Segmentation Medical Image Datasets Internal Medicine DOCTOR

May 24, 2023

Deep Learning-based Bio-Medical Image Segmentation using UNet Architecture and Transfer Learning
Nima Hassanpour, Abouzar Ghavami
Transfer Learning Image Segmentation Medical Image Datasets Deep Learning Based Medical Unet Based Segmentation UNet Architecture

May 12, 2023

Unlocking the Potential of Medical Imaging with ChatGPT's Intelligent Diagnostics
Ayyub Alzahem, Shahid Latif, Wadii Boulila, Anis Koubaa
Artificial Intelligence ChatGPT Generated Conversation Medical Image Full Potential Medical Imaging Medical Image Datasets Report Generation Automatic Diagnosis Large Scale Medical

April 23, 2023

Vision Transformer for Efficient Chest X-ray and Gastrointestinal Image Classification
Smriti Regmi, Aliza Subedi, Ulas Bagci, Debesh Jha
Convolutional Neural Network Vision Transformer Medical Image Analysis Medical Image Datasets Different Convolutional Neural Network Medical Image Analysis Task Gastrointestinal Tract

April 20, 2023

April 14, 2023

Scale Federated Learning for Label Set Mismatch in Medical Image Classification
Zhipeng Deng, Luyang Luo, Hao Chen
Federated Learning Medical Image Classification Medical Image Datasets Medical Domain

April 6, 2023

Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models
Mitchell Pavlak, Nathan Drenkow, Nicholas Petrick, Mohammad Mehdi Farhangi, Mathias Unberath
Absolute Stance Bias Medical Image Datasets Model Bias Skin Lesion Algorithm Auditing Task Model Data Auditing

March 29, 2023

Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation
Hieu H. Pham, Khiem H. Le, Tuan V. Tran, Ha Q. Nguyen
Anomaly Detection Object Detection Empirical Study Medical Image Analysis Medical Image Datasets Individual Annotator Multi Annotator

March 17, 2023

Preventing Unauthorized AI Over-Analysis by Medical Image Adversarial Watermarking
Xingxing Wei, Bangzheng Pu, Shiji Zhao, Chen Chi, Huazhu Fu
Medical Image Medical Image Datasets Adversarial Watermarking

March 9, 2023

An Evaluation of Non-Contrastive Self-Supervised Learning for Federated Medical Image Analysis
Soumitri Chattopadhyay, Soham Ganguly, Sreejit Chaudhury, Sayan Nag, Samiran Chattopadhyay
Medical Image Analysis Medical Image Datasets Federated Self Supervised Learning Non Contrastive Self Supervised Learning Federated Medical Image Segmentation

March 3, 2023

March 2, 2023

BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs
Sheng Zhang, Yanbo Xu, Naoto Usuyama, Hanwen Xu, Jaspreet Bagga, Robert Tinn, Sam Preston, Rajesh Rao, Mu Wei, Naveen Valluri, Cliff Wong, Andrea Tupini, Yu Wang, Matt Mazzola, Swadheen Shukla, Lars Liden, Jianfeng Gao, Matthew P. Lungren, Tristan Naumann, Sheng Wang, Hoifung Poon
Foundation Model Image Text Pair Medical Image Datasets Image Text

February 16, 2023

Revisiting Hidden Representations in Transfer Learning for Medical Imaging
Dovile Juodelyte, Amelia Jiménez-Sánchez, Veronika Cheplygina
Deep Learning Transfer Learning Supervised ImageNet Medical Imaging Medical Image Datasets Hidden Representation

Medical Image Datasets

Papers

Class Attention to Regions of Lesion for Imbalanced Medical Image Recognition

PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification

See Through the Fog: Curriculum Learning with Progressive Occlusion in Medical Imaging

Medical Federated Model with Mixture of Personalized and Sharing Components

Utilizing Segment Anything Model For Assessing Localization of GRAD-CAM in Medical Imaging

Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation

Deep Learning-based Bio-Medical Image Segmentation using UNet Architecture and Transfer Learning

Unlocking the Potential of Medical Imaging with ChatGPT's Intelligent Diagnostics

Vision Transformer for Efficient Chest X-ray and Gastrointestinal Image Classification

Medical Image Deidentification, Cleaning and Compression Using Pylogik

Segment Anything Model for Medical Image Analysis: an Experimental Study

Scale Federated Learning for Label Set Mismatch in Medical Image Classification

Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models

Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation

Preventing Unauthorized AI Over-Analysis by Medical Image Adversarial Watermarking

An Evaluation of Non-Contrastive Self-Supervised Learning for Federated Medical Image Analysis

Exploring Self-Supervised Representation Learning For Low-Resource Medical Image Analysis

Spatio-Temporal Structure Consistency for Semi-supervised Medical Image Classification

BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Revisiting Hidden Representations in Transfer Learning for Medical Imaging