# deepmedic/deepmedic

Efficient Multi-Scale 3D Convolutional Neural Network for Segmentation of 3D Medical Scans

Repository: https://github.com/deepmedic/deepmedic
Canonical: https://ross.abutalabs.com/products/deepmedic
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: deep-learning, machine-learning, medical-imaging, neural-networks, convolutional-neural-networks
Last push: 2024-08-04T12:23:09+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3781, "days_push": 759, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1063, forks 341 (observed 2026-08-28T04:03:26.371187+00:00)

## What it is
DeepMedic is an efficient multi-scale 3D convolutional neural network for segmenting 3D medical scans such as MRI and CT. It is a Python-based research tool originally developed for brain lesion segmentation.

## Use cases
- segment brain MRI scans for lesions
- 3D medical image segmentation with CNNs
- run multi-scale 3D CNN on CT volumes
- segment tumors in medical scans
- research on 3D convolutional neural networks for medical imaging

## When to choose
- you need proven 3D CNN segmentation for medical volumes like MRI or CT
- you want a lightweight, CPU/GPU-friendly tool for brain lesion segmentation
- you are doing medical imaging research and need a reproducible baseline model

## When to avoid
- you need a general-purpose deep learning framework for arbitrary tasks
- you want actively developed state-of-the-art segmentation models like nnU-Net
- you need 2D image segmentation or non-medical computer vision

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, machine-learning, image-processing, computer-vision
- domain: deep-learning, machine-learning, healthcare, image-processing
- platform: python
- tags: medical-imaging, 3d-segmentation, cnn, brain-mri, multi-scale, linux, gpu

## Member repositories
- deepmedic/deepmedic (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:26.371187+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:56:38.745854+00:00, confidence not recorded.
  - readme: https://github.com/deepmedic/deepmedic (fetched 2026-08-28T04:03:26.371187+00:00, sha ca8679f97c20)
- Data as of 2026-08-30T08:39:29.467469+00:00.