OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages

Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics

Deep Learning to Improve Breast Cancer Detection on Screening Mammography

Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk

dcmqi (DICOM for Quantitative Imaging) is a free, open source C++ library for conversion between imaging research formats and the standard DICOM representation for image analysis results

AI-based pathology predicts origins for cancers of unknown primary - Nature

DCE MRI analysis in Julia

Open source of Pyradiomics extension

Python Implementation of the CoLlAGe radiomics descriptor. CoLlAGe captures subtle anisotropic differences in disease pathologies by measuring entropy of co-occurrences of voxel-level gradient orientations on imaging computed within a local neighborhood.

Probabilistic topic model for identifying cellular micro-environments.

Code accompanying our ICVGIP 2016 paper

Predict survival time from PET scans

Clinically-Interpretable Radiomics [MICCAI'22, CMPB'21]

Python Open-source package for medical images processing and radiomics features extraction.

Skin cancer classification using transfer learning

In this project, we deploy the Bayesian Convolution Neural Networks (BCNN), proposed by Gal and Ghahramani [2015] to classify microscopic images of blood samples (lymphocyte cells). The data contains 260 microscopic images of cancerous and non-cancerous lymphocyte cells. We experiment with different network structures to obtain the model that re…

Implementation of a classification algorithm which accurately identifies cervix type based on images for Kaggle challenge using Keras

Bayesian Non-Parametric Image Segmentation using HDP-MRF

Deep ConvNets based eye cancer detection

Track 2D cell motion and mitosis in time-lapse microscopy