English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  SUITer: An automated method for improving segmentation of infratentorial structures at ultra‐high‐field MRI

El Mendili, M. M., Petracca, M., Podranski, K., Fleysher, L., Cocozza, S., & Inglese, M. (2020). SUITer: An automated method for improving segmentation of infratentorial structures at ultra‐high‐field MRI. Journal of Neuroimaging, 30(1), 28-39. doi:10.1111/jon.12672.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/21.11116/0000-0005-0B94-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-9E28-D
Genre: Journal Article

Files

show Files

Locators

show

Creators

show
hide
 Creators:
El Mendili, Mohamed Mounir1, Author
Petracca, Maria1, Author
Podranski, Kornelius1, 2, Author              
Fleysher, Lazar1, 3, Author
Cocozza, Sirio1, Author
Inglese, Matilde1, 4, 5, 6, Author
Affiliations:
1Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA, ou_persistent22              
2Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              
3Department of Advanced Biomedical Sciences, University of Naples Federico II, Italy, ou_persistent22              
4Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA, ou_persistent22              
5Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA, ou_persistent22              
6Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Perinatal Sciences, University of Genova, Italy, ou_persistent22              

Content

show
hide
Free keywords: Brainstem; Cerebellum; High spatial resolution; Parcellation; Ultra-high-field MRI
 Abstract: BACKGROUND AND PURPOSE: The advent of high and ultra-high-field MRI has significantly improved the investigation of infratentorial structures by providing high-resolution images. However, none of the publicly available methods for cerebellar image analysis has been optimized for high-resolution images yet. METHODS: We present the implementation of an automated algorithm—SUITer (spatially unbiased infratentorial for enhanced resolution) method for cerebellar lobules parcellation on high-resolution MR images acquired at both 3 and 7T MRI. SUITer was validated on five manually segmented data and compared with SUIT, FreeSurfer, and convolutional neural networks (CNN). SUITer was then applied to 3 and 7T MR images from 10 multiple sclerosis (MS) patients and 10 healthy controls (HCs). RESULTS: The difference in volumes estimation for the cerebellar grey matter (GM), between the manual segmentation (ground truth), SUIT, CNN, and SUITer was reduced when computed by SUITer compared to SUIT (5.56 vs. 29.23 mL) and CNN (5.56 vs. 9.43 mL). FreeSurfer showed low volumes difference (3.56 mL). SUITer segmentations showed a high correlation (R 2 = .91) and a high overlap with manual segmentations for cerebellar GM (83.46%). SUITer also showed low volumes difference (7.29 mL), high correlation (R 2 = .99), and a high overlap (87.44%) for cerebellar GM segmentations across magnetic fields. SUITer showed similar cerebellar GM volume differences between MS patients and HC at both 3T and 7T (7.69 and 7.76 mL, respectively). CONCLUSIONS: SUITer provides accurate segmentations of infratentorial structures across different resolutions and MR fields.

Details

show
hide
Language(s): eng - English
 Dates: 2019-10-112019-06-062019-10-112019-11-052020-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1111/jon.12672
PMID: 31691416
Other: Epub 2019
 Degree: -

Event

show

Legal Case

show

Project information

show hide
Project name : -
Grant ID : CNS‐2014‐221
Funding program : -
Funding organization : TEVA Neuroscience

Source 1

show
hide
Title: Journal of Neuroimaging
  Other : J. Neuroimaging
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Boston, Mass. : Blackwell Publishers Ltd.
Pages: - Volume / Issue: 30 (1) Sequence Number: - Start / End Page: 28 - 39 Identifier: ISSN: 1051-2284
CoNE: https://pure.mpg.de/cone/journals/resource/954925593485