explaingit

msx00/cor-fem

Analysis updated 2026-05-18

15PythonAudience · researcherComplexity · 4/5Setup · hard

TLDR

A research tool that uses a physics based simulation method to align two 3D medical scans of the same organ, currently tuned for the prostate.

Mindmap

mindmap
  root((Cor-FEM))
    What it does
      Non-rigid registration
      Finite element method
      Prostate scans
    Tech stack
      Python
      Blender
      FEM
    Use cases
      Align 3D scans
      Build mesh from volume
      Compare to other FEM methods
    Audience
      Medical researchers
      Imaging scientists
    Setup
      Ubuntu preferred
      Edit shell script paths
      No license yet

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Align two 3D prostate scans of the same patient taken at different times.

USE CASE 2

Convert a 3D medical volume file into a smoothed surface mesh for further processing.

USE CASE 3

Compare this registration method's speed against other published FEM based methods.

USE CASE 4

Use as a starting point for research into non-rigid registration of other organs.

What is it built with?

PythonFEMBlender

How does it compare?

msx00/cor-fem13127905/deep-learning-based-air-gesture-text-recognition-6xvl/paralives-plugins-index
Stars151515
LanguagePythonPythonPython
Setup difficultyhardmoderateeasy
Complexity4/53/52/5
Audienceresearcherdevelopergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Needs prostate scan data in a specific volume format, path edits in the shell script, and Blender for some steps.

No license has been published yet, so by default you do not have permission to reuse, modify, or redistribute this code.

In plain English

Cor-FEM is a research tool for medical image registration, which means lining up two 3D scans of the same body part so they match up even when the shape has changed between scans. It uses a technique called the finite element method, a way of modeling how soft, flexible material bends and deforms, to handle non-rigid registration, where the organ is not just moved or rotated but also stretched or squeezed. The authors say this is one of the first non-linear versions of this approach built for a specific technical setting called zero boundary condition. Right now the released version is built specifically for prostate scans, though the authors plan to add settings for the kidney, liver, and other abdominal organs later. The overall pipeline takes a 3D medical volume file, such as a nii, nii.gz, or nrrd scan, and turns it into a surface mesh, smooths that mesh, and then runs the registration step to line it up against another scan. Three main scripts handle this: volume2mesh.py builds the mesh from the volume, mesh_smooth.py cleans it up, and cor-fem-prostate.sh runs the actual registration. The README reports that on a public prostate dataset called mu-RegPro, this method ran faster on average than three other named FEM-based registration methods it was compared against. The code is mainly built and tested on Ubuntu, though Windows is allowed if you turn off the Blender-related parts of the code first. The project is written in Python, has 15 stars, and is explicitly aimed at research use rather than production or clinical use. The authors note that file paths in the shell script need to be checked and edited before running, and that registration settings may need adjusting for different organs, scan types, and image resolutions. The README states that citation information and license details will be added later, so neither is available yet.

Copy-paste prompts

Prompt 1
Explain what volume2mesh.py does in Cor-FEM and what input file formats it accepts.
Prompt 2
Walk me through running the cor-fem-prostate.sh pipeline on my own prostate scan data.
Prompt 3
Help me disable the Blender-related functions in Cor-FEM so it runs on Windows.
Prompt 4
Summarize how Cor-FEM's runtime compares to GMM-FEM, Adjoint-elastic, and BCF-FEM on the mu-RegPro dataset.

Frequently asked questions

What is cor-fem?

A research tool that uses a physics based simulation method to align two 3D medical scans of the same organ, currently tuned for the prostate.

What language is cor-fem written in?

Mainly Python. The stack also includes Python, FEM, Blender.

What license does cor-fem use?

No license has been published yet, so by default you do not have permission to reuse, modify, or redistribute this code.

How hard is cor-fem to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is cor-fem for?

Mainly researcher.

Open on GitHub → Explain another repo

This repo across BitVibe Labs

Verify against the repo before relying on details.