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.
Tunable U-Net implementation in PyTorch
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
ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection
Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images
Read and write Neuroglancer datasets programmatically.
Datasets, Transforms and Utilities specific to Biomedical Imaging
Codes that I have written to complete promise12 prostate segmentation competition.
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.
Rank3 Code for ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection, Task 3
Scientific Reports 2023
Smart India Hackathon 2019 project given by the Department of Atomic Energy
A Python library for biomedical statistical shape and appearance modelling.
Histomic Prognostic Signature (HiPS): A population-level computational histologic signature for invasive breast cancer prognosis
Complete U-net Implementation with keras
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