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DRLSE-Image-Segmentation

imported

software/drlse-image-segmentation

Distance Regularized Level Set Evolution and Its Application to Image Segmentation

Machine-generated from the listed sources and not yet reviewed by a human.

DRLSE-Image-Segmentation project image
GitHub preview card for balcilar/DRLSE-Image-Segmentation. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Repository
github.com/balcilar/DRLSE-Image-Segmentation
Documentation
unknown
Tags
image-processing · image-segmentation · level-set · matlab · medical-imaging
Regulatory
unknown
built by · 1

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

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    Computes vesselness scores for 3-dimensional images.

  • HippMapp3rimage-processing · image-segmentation · medical-imaging

    AICONSlab's hippocampal segmentation algorithm using CNNs

  • BiaPyimage-processing · image-segmentation

    Open source Python library for building bioimage analysis pipelines

  • PyHistologyimage-processing · image-segmentation

    Python package that uses colorspace-based segmentation to analyze histopathology images.

  • smriprepimage-processing · image-segmentation

    Structural MRI PREProcessing (sMRIPrep) workflows for NIPreps (NeuroImaging PREProcessing tools)

sources
  1. api.github.com/repos/balcilar/DRLSE-Image-Segmentation
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2019-10-31, 93 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/58.json→ .entries["drlse-image-segmentation"]

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