A collection of resources on applications of multi-modal learning in medical imaging.

Foundation models based medical image analysis

Awesome radiology report generation and image captioning papers.

Code for the paper "ORGAN: Observation-Guided Radiology Report Generation via Tree Reasoning" (ACL'23).

Code used for the MLMI 2021 paper Clinically Correct Report Generation from Chest X-Rays Using Templates

Code for the paper "RECAP: Towards Precise Radiology Report Generation via Dynamic Disease Progression Reasoning" (EMNLP'23 Findings).

Code for the paper "ICON: Improving Inter-Report Consistency in Radiology Report Generation via Lesion-aware Mixup Augmentation" (EMNLP'24 Findings).

Code for the paper "RADAR: Enhancing Radiology Report Generation with Supplementary Knowledge Injection" (ACL'25).

[IJBHI 2024] This is the official implementation of CAMANet: Class Activation Map Guided Attention Network for Radiology Report Generation accepted to IEEE Journal of Biomedical and Health Informatics (J-BHI), 2023.

GPT-2 based medical reports generator for X-ray images in Czech.

Medical Report Generation And VQA (Adapting XrayGPT to Any Modality)

AI-powered Chest X-ray report generation app using VLM (Swin-T5) and LLM (LLaMA-3) for multilingual Q&A and medical education support.

Resources on the use of multimodal learning in medical imaging.

The primary objective of this work is to develop an innovative system capable of providing explainable brain tumor detection.

HealthSummarizeAI is an innovative NLP-based tool designed to transform the way healthcare professionals interact with electronic health records (EHR). By leveraging advanced entity recognition and text summarization techniques, HealthSummarize efficiently extracts and condenses critical information .

This is the official implementation of MvKeTR: Chest CT Report Generation with Multi-View Perception and Knowledge Enhancement accepted to IEEE Journal of Biomedical and Health Informatics (J-BHI), 2025.