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chevron_left Image-analysis libraries Image visualization Image data analysis Image segmentation chevron_right
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MITK specifications

Information


Unique identifier OMICS_17375
Name MITK
Alternative name Medical Imaging Toolkit
Software type Toolkit/Suite
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C++
License BSD 3-clause “New” or “Revised” License
Computer skills Advanced
Stability Stable
Maintained Yes

Subtool


  • MITK-ModelFit

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Versioning


No version available

Maintainer


  • person_outline Ivo Wolf <>

Additional information


https://github.com/MITK/MITK

Publications for Medical Imaging Toolkit

MITK citations

 (9)
library_books

Impact of 18F FET PET on Target Volume Definition and Tumor Progression of Recurrent High Grade Glioma Treated with Carbon Ion Radiotherapy

2018
PMCID: 5940831
PMID: 29740097
DOI: 10.1038/s41598-018-25350-7

[…] gadoterate meglumine (dotarem, guerbet, france) as well as axial flair and axial t2-weighted images (slice thickness 5 mm)., image processing was done using the medical imaging interaction toolkit mitk (www.mitk.org). mitk is an open-source software framework for medical image procession and image analysis. its toolkit nature allows for expansion with own implementations. mitk offers […]

library_books

Visualization of 4D multimodal imaging data and its applications in radiotherapy planning

2017
PMCID: 5689910
PMID: 29082656
DOI: 10.1002/acm2.12209

[…] and extensions for multivolume visualization, for instance, have not found their way into the framework yet. research platforms, such as 3d slicer and the medical imaging interaction toolkit (mitk) which are tailored to medical applications often use vtk as basis for the visualization. they offer solutions to more specific clinical applications or workflows, but they also target data […]

library_books

2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non Small Cell Lung Cancer

2017
PMCID: 5605492
PMID: 28930698
DOI: 10.1016/j.tranon.2017.08.007

[…] with manual segmentation. particularly, the segmentation algorithm performed well for ground-glass nodules (86% compared to the radiologists). this algorithm has been programmed as an add-on in the medical imaging toolkit (mitk), which is a c++ library for integrated medical image processing and is developed by the institute of automation, chinese academy of sciences . finally, 3d regions […]

library_books

Post Mortem Validation of MRI Identified Veins on the Surface of the Cerebral Cortex as Potential Landmarks for Neurosurgery

2017
PMCID: 5478689
PMID: 28680389
DOI: 10.3389/fnins.2017.00355

[…] (fedorov et al., ). 3d visualization of surface veins on cadaver 2 was performed using a manually created brain mask, based on the magnitude data, and the medical imaging interaction toolkit (www.mitk.org) (wolf et al., )., cadaver heads were stored at 4°c between mr measurements and removal of the brain, which was performed within 12 h. prior to the craniotomy, the cervical part […]

library_books

Comparison of DCE‐MRI kinetic parameters and FMISO‐PET uptake parameters in head and neck cancer patients

2017
PMCID: 5485084
PMID: 28317128
DOI: 10.1002/mp.12228

[…] compartment model with three rate constants. dce‐mr images were analyzed with the extended tofts model. segmentation of common carotid arteries for input function extraction was done with the mitk software. kinetic analysis was done with a custom‐developed program in matlab (the mathworks, natick, ma, usa)., after registering the fmiso‐pet images to the downsampled dce‐mr image, […]

library_books

A Review on Real Time 3D Ultrasound Imaging Technology

2017
PMCID: 5385255
PMID: 28459067
DOI: 10.1155/2017/6027029

[…] updated immediately to users to provide the quantitative feedback while ir is used to drive the volume rendering as the ir exceeds a predefined threshold. the researchers used a module provided by medical imaging toolkit (mitk) for the rendering. the reconstruction and visualization are all performed on a personal computer. they set the ir threshold to 5% and achieved a visualization rate […]


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MITK institution(s)
Deutsches Krebsforschungszentrum (DKFZ), Div. Medical and Biological Informatics, Heidelberg, Germany
MITK funding source(s)
This work was supported by the Deutsche Forschungsgemeinschaft (DFG) and by the Tumorzentrum Heidelberg/Mannheim.

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