biomedical-image-processing

Tools for computational pathology

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

Visual Med-Alpaca is an open-source, multi-modal foundation model designed specifically for the biomedical domain, built on the LLaMa-7B.

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

PyTorch Connectomics: segmentation toolbox for EM connectomics

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

Read and write Neuroglancer datasets programmatically.

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

Open source Python library for building bioimage analysis pipelines

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

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.

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