Medical Image

Medical image analysis focuses on extracting meaningful information from various imaging modalities (e.g., CT, MRI, X-ray) to improve diagnosis and treatment planning. Current research emphasizes developing robust and efficient algorithms, often employing convolutional neural networks (CNNs), transformers, and diffusion models, to address challenges like data variability, limited annotations, and privacy concerns. These advancements are crucial for improving the accuracy and speed of medical image analysis, leading to better patient care and accelerating medical research.

Papers

June 20, 2023

KiUT: Knowledge-injected U-Transformer for Radiology Report Generation
Zhongzhen Huang, Xiaofan Zhang, Shaoting Zhang
Medical Image Radiology Report Generation Report Generation Knowledge Injected U Transformer

June 18, 2023

Generation of Radiology Findings in Chest X-Ray by Leveraging Collaborative Knowledge
Manuela Daniela Danu, George Marica, Sanjeev Kumar Karn, Bogdan Georgescu, Awais Mansoor, Florin Ghesu, Lucian Mihai Itu, Constantin Suciu, Sasa Grbic, Oladimeji Farri, Dorin Comaniciu
Medical Image Faithful Generation Chest X Ray Radiology Report Generation Radiology Report Radiology Workflow

June 16, 2023

June 15, 2023

Temporally-Extended Prompts Optimization for SAM in Interactive Medical Image Segmentation
Chuyun Shen, Wenhao Li, Ya Zhang, Xiangfeng Wang
Medical Image Segmentation Medical Image Segment Anything Model Image Segmentation Prompt Optimization Anything Model

June 13, 2023

Visual Question Answering (VQA) on Images with Superimposed Text
Venkat Kodali, Daniel Berleant
Medical Image Visual Question Answering 3d Vqa Text Annotation VQA Task VQA Benchmark

June 12, 2023

Active Globally Explainable Learning for Medical Images via Class Association Embedding and Cyclic Adversarial Generation
Ruitao Xie, Jingbang Chen, Limai Jiang, Rui Xiao, Yi Pan, Yunpeng Cai
Generative Adversarial Network Medical Image Explainable Artificial Intelligence Class Specific Feature Class Embeddings Active Learning With Contrastive Explanation

June 10, 2023

June 2, 2023

Transformer-based Annotation Bias-aware Medical Image Segmentation
Zehui Liao, Yutong Xie, Shishuai Hu, Yong Xia
Medical Image Segmentation Medical Image Annotation Bias Bias Annotation

June 1, 2023

May 31, 2023

May 30, 2023

Medical Image

Papers

KiUT: Knowledge-injected U-Transformer for Radiology Report Generation

Generation of Radiology Findings in Chest X-Ray by Leveraging Collaborative Knowledge

Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback

Label-noise-tolerant medical image classification via self-attention and self-supervised learning

Temporally-Extended Prompts Optimization for SAM in Interactive Medical Image Segmentation

Visual Question Answering (VQA) on Images with Superimposed Text

Active Globally Explainable Learning for Medical Images via Class Association Embedding and Cyclic Adversarial Generation

Online learning for X-ray, CT or MRI

AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder

Federated Learning for Medical Image Analysis: A Survey

On the Challenges and Perspectives of Foundation Models for Medical Image Analysis

Customizing General-Purpose Foundation Models for Medical Report Generation

Transformer-based Annotation Bias-aware Medical Image Segmentation

Using generative AI to investigate medical imagery models and datasets

A Transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics

Introduction to Medical Imaging Informatics

Additional Positive Enables Better Representation Learning for Medical Images

Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model

Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images

An Evaluation of Lightweight Deep Learning Techniques in Medical Imaging for High Precision COVID-19 Diagnostics