pcallec

Paul Calle's starred repositories

Awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

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ai-science-training-series

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Awasome-Pruning

Awasome Papers and Resources in Deep Neural Network Pruning with Source Code.

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connected-components-3d

Connected components on discrete and continuous multilabel 3D & 2D images. Handles 26, 18, and 6 connected variants; periodic boundaries (4, 8, & 6)

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ESP-MedSAM

[ArXiv' 24] ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image Segmentation

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MultiTalent

Implemention of the Paper "MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation"

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segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

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I-MedSAM

[ECCV2024] I-MedSAM: Implicit Medical Image Segmentation with Segment Anything

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MedMNIST

[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification

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Please-Contain-Yourself

A Docker tutorial written for people who don't actually know Docker already.

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segmentation_models.pytorch

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

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MedSAM

Segment Anything in Medical Images

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Meta-Co-Training

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GaNDLF

A generalizable application framework for segmentation, regression, and classification using PyTorch

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dicom2nifti

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TotalSegmentator

Tool for robust segmentation of >100 important anatomical structures in CT and MR images

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3DCT-SD-IVH-ICH

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DeSD

MICCAI 2022 Paper

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3DGAN_CT_Segmentation

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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.

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Visualising-Image-Classification-Models-and-Saliency-Maps

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pytorch-unsupervised-segmentation

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pytorch-grad-cam

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

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