ITK-SNAP statistics

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Citations per year

Number of citations per year for the bioinformatics software tool ITK-SNAP

Tool usage distribution map

This map represents all the scientific publications referring to ITK-SNAP per scientific context
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Associated diseases

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ITK-SNAP specifications


Unique identifier OMICS_26149
Software type Application/Script
Interface Graphical user interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++
Computer skills Medium
Version 3.6.0
Stability Stable
Registration required Yes
Maintained Yes




No version available



  • person_outline Paul Yushkevich

Additional information

Publication for ITK-SNAP

ITK-SNAP citations


Assessing the kidney function parameters glomerular filtration rate and effective renal plasma flow with dynamic FDG PET/MRI in healthy subjects

PMCID: 5943199
PMID: 29744748
DOI: 10.1186/s13550-018-0389-1

[…] he basis of a method described by Khalighi et al. [, ] with the dataset of the subjects from subject group 2, who additionally had contrast-enhanced MRI examination. The active contour algorithm from ITK snap (version 3.6.0) was used to extract the aorta volume VA from the contrast-enhanced MR data. Spill-out region was defined by summing up the early PET frames and segmenting the aorta from the s […]


Automatic brain tissue segmentation based on graph filter

BMC Med Imaging
PMCID: 5941431
PMID: 29739350
DOI: 10.1186/s12880-018-0252-x

[…] th a noise level of 9% and an INU level of 40% from the BrainWeb dataset. In the figure, the 2D axial, sagittal and coronal views of 3D segmentation results are shown for visual inspections using the itk-snap tool []. The first and second columns are the image and the ground truth of the segmentation with red, green, blue voxels corresponding to CSF, GM and WM tissues, respectively. The third, fou […]


Left Ventricular Trabeculations Decrease the Wall Shear Stress and Increase the Intra Ventricular Pressure Drop in CFD Simulations

Front Physiol
PMCID: 5936785
PMID: 29760665
DOI: 10.3389/fphys.2018.00458

[…] ame outline for both the smoothed and detailed geometries.The control LV, as a representative of a state of the art anatomical model, was reconstructed using a regularized region growing algorithm of ITK-SNAP (ITK-SNAP Medical Image Segmentation Tool, RRID:SCR_002010) to get only large scale anatomical detail from the images. The algorithm allowed controlling the smoothness of the extracted contou […]


Resting state fMRI study of brain activation using low intensity repetitive transcranial magnetic stimulation in rats

Sci Rep
PMCID: 5928106
PMID: 29712947
DOI: 10.1038/s41598-018-24951-6

[…] s to the middle volume of a serial acquisition; and (iii) reorienting the brain into left-anterior-superior (LAS) axes (radiological view). Intracranial binary brain masks were created manually using ITK-SNAP 3.4.0 ( for each functional and anatomical dataset and were used to extract the brain using the flsmaths tool. Post-stimulation images were co-registered to the baseline fMRI […]


Differential Medial Temporal Lobe and Parietal Cortical Contributions to Real world Autobiographical Episodic and Autobiographical Semantic Memory

Sci Rep
PMCID: 5906442
PMID: 29670138
DOI: 10.1038/s41598-018-24549-y
call_split See protocol

[…] ects), and bilateral anatomically defined ROIs within the MTL (hippocampal head, body, and tail; perirhinal cortex - PRC; parahippocampal cortex - PHC). Anatomical ROIs were manually traced using the ITK-SNAP software package ( using established procedures,–. Using parameter estimates extracted from these ROIs, we examined their functional activation profiles across the auto […]


Temporomandibular joint regeneration: proposal of a novel treatment for condylar resorption after orthognathic surgery using transplantation of autologous nasal septum chondrocytes, and the first human case report

PMCID: 5889586
PMID: 29625584
DOI: 10.1186/s13287-018-0806-4

[…] The acquired images were saved in DICOM file format that can construct three-dimensional volumetric files of the regions of interest for superposition, a process known as segmentation. Therefore, the ITK-SNAP 3.6 software ( was applied. Three-dimensional surface mesh models of the right and left mandibular condyles at T1 and T2 were constructed by outlining the cortical boundaries […]

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ITK-SNAP institution(s)
Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, PA, USA; Departments of Computer Science and Psychiatry, University of North Carolina, NC, USA; Neurodevelopmental Disorders Research Center, University of North Carolina, NC, USA
ITK-SNAP funding source(s)
Supported by Cognitica Corporation under NIH/NLM PO 467-MZ-202446-1, the NIH/NIBIB P01 EB002779, NIH Conte Center MH064065, and UNC Neurodevelopmental Disorders Research Center, Developmental Neuroimaging Core.

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