Shape-appearance constrained segmentation and separation of vein and artery in pulsatile tinnitus patients based on MR angiography and flow MRI.


Journal

Magnetic resonance imaging
ISSN: 1873-5894
Titre abrégé: Magn Reson Imaging
Pays: Netherlands
ID NLM: 8214883

Informations de publication

Date de publication:
09 2019
Historique:
received: 14 02 2019
revised: 03 05 2019
accepted: 19 05 2019
pubmed: 5 6 2019
medline: 3 1 2020
entrez: 5 6 2019
Statut: ppublish

Résumé

This study reports on the development and evaluation of a novel segmentation method for extracting the internal jugular vein and the adjacent carotid artery from magnetic resonance (MR) images of patients with pulsatile tinnitus. A narrow band level set method with combined shape and appearance constraints was developed and applied to high-resolution MR images from 17 pulsatile tinnitus patients (age 52 ± 23 years, 10 females). The proposed method was validated by comparing with the manual segmentation as well as by identifying the jugular vein and carotid artery based on 4D flow MRI in which the two types of vessels have opposing flow. Our study showed that the vein and artery are in contact with each other on 30.2% of all the slices. Dice value, Peak signal-to-noise ratio (PSNR), Hausdorff distance and mean sum of square distance (MSSD) between automatic and manual segmentation were 89.13 ± 2.84%, 27.36 ± 2.39%, 17.2 ± 6.9 mm, 7.4 ± 5.5 mm, demonstrating good segmentation accuracy. The average Dice similarity coefficient and the coefficient of variation compared with 4D flow MRI was 91.42 ± 1.63% and 89.28 ± 4.54% for the internal jugular vein and the carotid artery. The present pipeline for automatic internal jugular vein quantification holds promise for efficient image interpretation in large-scale cohort studies.

Identifiants

pubmed: 31163188
pii: S0730-725X(19)30104-3
doi: 10.1016/j.mri.2019.05.026
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

187-195

Subventions

Organisme : NHLBI NIH HHS
ID : R01 HL114118
Pays : United States
Organisme : NHLBI NIH HHS
ID : R56 HL133663
Pays : United States

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Yan Wang (Y)

Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, United States.

Evan Kao (E)

Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, United States.

Yue Zhang (Y)

Department of Surgery, University of California San Francisco, CA, United States; Veteran Affairs Medical Center, San Francisco, CA, United States.

Bing Tian (B)

Department of Radiology, Changhai Hospital of Shanghai, Shanghai, China. Electronic address: bing.tian@hotmail.com.

Jingshan Gong (J)

Department of Radiology, Shenzhen People's Hospital, Shenzhen, China.

Farshid Faraji (F)

Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, United States.

Henrik Haraldsson (H)

Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, United States.

Matthew R Amans (MR)

Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, United States.

David Saloner (D)

Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, United States; Veteran Affairs Medical Center, San Francisco, CA, United States.

Jing Liu (J)

Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, United States.

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