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; periodic boundaries (4, 8, & 6)

Tunable U-Net implementation in PyTorch

Euclidean distance & signed distance transform for multi-label 3D anisotropic images using marching parabolas.

Python based dashboard for real-time Electrical Impedance Tomography including image reconstruction using Back Projection, Graz Consensus and Gauss Newton methods

3D Unet biomedical segmentation model powered by tensorpack with fast io speed

PyTorch Connectomics: segmentation toolbox for EM connectomics

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

A PyTorch-based library for working with 3D and 2D convolutional neural networks, with focus on semantic segmentation of volumetric biomedical image data

Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network and Pretrained Models

Skeletonize densely labeled 3D image segmentations with TEASAR. (Medial Axis Transform)

Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images

Read and write Neuroglancer datasets programmatically.

ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection

Open source Python library for building bioimage analysis pipelines

Datasets, Transforms and Utilities specific to Biomedical Imaging

Codes that I have written to complete promise12 prostate segmentation competition.

Developing a UNet3D model for accurate MRI skull stripping using the Calgary Campinas 359 dataset, enhancing neuroimaging preprocessing workflows.

Dijkstra's Shortest Path for 6, 18, and 26-Connected 3D (Volumetric) Image Volumes