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osparc-iseg

The Medical Image Segmentation Tool Set (iSEG) is a fully integrated segmentation (including pre- and postprocessing) toolbox for the efficient, fast, and flexible generation of anatomical models from various types of imaging data

https://github.com/itisfoundation/osparc-iseg

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
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    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.4%) to scientific vocabulary

Keywords

anatomical-models c-plus-plus dicom image-processing itk medical-image-processing medical-image-segmentation medical-imaging nifti plugins
Last synced: 6 months ago · JSON representation ·

Repository

The Medical Image Segmentation Tool Set (iSEG) is a fully integrated segmentation (including pre- and postprocessing) toolbox for the efficient, fast, and flexible generation of anatomical models from various types of imaging data

Basic Info
  • Host: GitHub
  • Owner: ITISFoundation
  • License: mit
  • Language: C++
  • Default Branch: master
  • Homepage:
  • Size: 8.65 MB
Statistics
  • Stars: 48
  • Watchers: 17
  • Forks: 15
  • Open Issues: 5
  • Releases: 5
Topics
anatomical-models c-plus-plus dicom image-processing itk medical-image-processing medical-image-segmentation medical-imaging nifti plugins
Created almost 8 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License Citation Codeowners

README.md

iSEG logo Build Actions Status DOI

Description

The Medical Image Segmentation Tool Set (iSEG) is a fully integrated segmentation (including pre- and postprocessing) toolbox for the efficient, fast, and flexible generation of anatomical models from various types of imaging data. iSEG includes a variety of semi-automatic segmentation methods. The key strengths of iSEG are a) a powerful set of tools for manual segmentation (correction), b) support for massive image sizes, c) suport for segmenting complex models with a large number of tissues, e.g. for inserting thin layers. It is the only powerful segmentation platform, which supports color images, e.g. from the NIH Visible Human or Visible Korean projects.

iSEG features a plugin mechanism, which allows users to easily extend the application with custom widgets. The development of iSEG has been driven by the Virtual Population project at the IT'IS Foundation, due to a lack of alternatives amongst open source and commercial tools.

Compilation instructions

A defined set of 3rd party libraries are required in order to compile iSEG. Instructions as to how these libraries must be installed and compiled are provided below.

Required applications

The applications below are needed in order to compile iSEG and its dependencies.

Required 3rd party libraries

The libraries below are required to be compiled and installed on the system in order to compile iSEG. Platform specific instructions for each library are given below.

Note

For installing EIGEN just download and extract the source code

Compiling iSEG

Owner

  • Name: IT'IS Foundation
  • Login: ITISFoundation
  • Kind: organization
  • Email: info@itis.swiss
  • Location: Zurich, Switzerland

Foundation for Research on Information Technologies in Society (IT'IS)

Citation (CITATION.cff) 

cff-version: 1.2.0
message: If you use this software, please cite it using these metadata.
title: iSEG Open Source
abstract: The Medical Image Segmentation Tool Set (iSEG) is a fully integrated segmentation (including pre- and postprocessing) toolbox for the efficient, fast, and flexible generation of anatomical models from various types of imaging data.
authors:
  - family-names: Lloyd
    given-names: Bryn
    orcid: "https://orcid.org/0000-0003-0935-9530"
  - family-names: Maiz
    given-names: Odei
    affiliation: "IT'IS Foundation"
  - family-names: Neufeld
    given-names: Esra
    orcid: "https://orcid.org/0000-0001-5528-6147"
  - family-names: Anderegg
    given-names: Sylvain
    affiliation: "IT'IS Foundation"
  - family-names: Guidon
    given-names: Manuel
    orcid: "https://orcid.org/0000-0003-3543-6683"
version: 1.2.2
date-released: "2022-05-16"
identifiers:
  - description: This is the collection of archived snapshots of all versions of iSEG
    type: doi
    value: "10.5281/zenodo.123456"
  - description: This is the archived snapshot of version 1.2.2 of iSEG
    type: doi
    value: "10.5281/zenodo.6563519"
  - description: This is the archived snapshot of version 1.2 of iSEG
    type: doi
    value: "10.5281/zenodo.6563514"
  - description: This is the archived snapshot of version 1.1 of iSEG
    type: doi
    value: "10.5281/zenodo.6563513"
  - description: This is the archived snapshot of version 1.0 of iSEG
    type: doi
    value: "10.5281/zenodo.6563511"
license: MIT license
repository-code: "https://github.com/ITISFoundation/osparc-iseg"

GitHub Events

Total
  • Watch event: 7
  • Fork event: 1
Last Year
  • Watch event: 7
  • Fork event: 1

Dependencies

.github/workflows/build.yml actions
  • actions/checkout v2 composite
docker/Dockerfile docker
  • ubuntu 18.04 build