pepperbubble

Charl1e's starred repositories

HERGen

[ECCV'2024] HERGen: Elevating Radiology Report Generation with Longitudinal Data

Language:Jupyter NotebookNOASSERTION1000

hi-ml

HI-ML toolbox for deep learning for medical imaging and Azure integration

Language:PythonMIT26400

ActionCLIP

This is the official implement of paper "ActionCLIP: A New Paradigm for Action Recognition"

Language:PythonMIT50900

MedST

Offical code of Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training[ICML 2024]

Language:Python1100

CVPR2024_MAVL

Multi-Aspect Vision Language Pretraining - CVPR2024

Language:Python5600

CLIP

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Language:Jupyter NotebookMIT2560100

The official code for MedKLIP: Medical Knowledge Enhanced Language-Image Pre-Training in Radiology. We propose to leverage medical specific knowledge enhancing language-image pre-training method, significantly advancing the ability of pre-trained models to handle unseen diseases on zero-shot classification and grounding tasks.

Language:Python14400

Applied-Deep-Learning

Applied Deep Learning Course

316000

KAD

Language:PythonMIT12100

CARZero

Language:PythonApache-2.02300

CheXzero

This repository contains code to train a self-supervised learning model on chest X-ray images that lack explicit annotations and evaluate this model's performance on pathology-classification tasks.

Language:PythonMIT17600

MRM-pytorch

An official implementation of Advancing Radiograph Representation Learning with Masked Record Modeling (ICLR'23)

Language:PythonMIT7300

plip

Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

Language:Python26700