There are 24 repositories under biomedical-image-processing topic.
Tools for computational pathology
Visual Med-Alpaca is an open-source, multi-modal foundation model designed specifically for the biomedical domain, built on the LLaMa-7B.
Connected components on discrete and continuous multilabel 3D & 2D images. Handles 26, 18, and 6 connected variants.
Tunable U-Net implementation in PyTorch
Euclidean distance & signed distance transform for multi-label 3D anisotropic images using marching parabolas.
3D Unet biomedical segmentation model powered by tensorpack with fast io speed
A PyTorch-based library for working with 3D and 2D convolutional neural networks, with focus on semantic segmentation of volumetric biomedical image data
PyTorch Connectomics: segmentation toolbox for EM connectomics
Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network and Pretrained Models
Read and write Neuroglancer datasets programmatically.
ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection
Datasets, Transforms and Utilities specific to Biomedical Imaging
Codes that I have written to complete promise12 prostate segmentation competition.
Dijkstra's Shortest Path for 6, 18, and 26-Connected 3D (Volumetric) Image Volumes
Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification
Scalable Optical Flow-based Image Montaging and Alignment
Rank3 Code for ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection, Task 3
Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.
Smart India Hackathon 2019 project given by the Department of Atomic Energy
UNet based model that segment retina to 8 layers in OCT images
Cancer Detection from Microscopic Images by Fine-tuning Pre-trained Models ("Inception") for new class labels
A Python library for biomedical statistical shape and appearance modelling.
WMH segmentaion with unet, dilated_unet, and with ideas from denseNet
Fracture Detection in Pediatric Wrist Trauma X-ray Images Using YOLOv8 Algorithm
Implementation of the paper titled - U-Net: Convolutional Networks for Biomedical Image Segmentation @ https://arxiv.org/abs/1505.04597
Segmenting WSIs using Deep Convolutional Neural Networks
Complete U-net Implementation with keras
A course in biomedical image analytics by Prof. Dmitry V. Dylov