Tools for computational pathology
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Updated
Nov 6, 2024 - Python
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
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)
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.
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
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