8 projects
boa-contrast
Computes CT contrast phase and GI tract contrast using TotalSegmentator and ML
kmsr
kMSR provides a selection of algorithms to solve the k-Min-Sum-Radii problem.
fair-kmeans
Fair K-Means produces a fair clustering assignment according to the fairness definition of Chierichetti et al. Each point has a binary color, and the goal is to assign the points to clusters such that the number of points with different colors in each cluster is the same and the cost of the clusters is minimized.
exact-kmeans
Computes an optimal k-means solution for small instances and small k.
flspp
Implementation of the FLS++ algorithm for K-Means clustering.
bico
BICO is a fast streaming algorithm to compute coresets for the k-means problem on very large sets of points.
fhir-pyrate
FHIR-PYrate is a package that provides a high-level API to query FHIR Servers for bundles of resources and return the structured information as pandas DataFrames. It can also be used to filter resources using RegEx and SpaCy and download DICOM studies and series.
body-organ-analysis
BOA is a tool for segmentation of CT scans developed by the SHIP-AI group at the Institute for Artificial Intelligence in Medicine (https://ship-ai.ikim.nrw/). Combining the TotalSegmentator and the Body Composition Analysis, this tool is capable of analyzing medical images and identifying the different structures within the human body, including bones, muscles, organs, and blood vessels.
