Substantia nigra segmentation on neuromelanin-sensitive MRI

Touseef Ahmad Qureshi; Elliot Hogg; Cody Lynch; Debiao Li; Michele Tagliati; Zhaoyang Fan

doi:10.1117/12.2512909

15 March 2019 Substantia nigra segmentation on neuromelanin-sensitive MRI

Touseef Ahmad Qureshi, Elliot Hogg, Cody Lynch, Debiao Li, Michele Tagliati, Zhaoyang Fan

Proceedings Volume 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging; 109530Y (2019) https://doi.org/10.1117/12.2512909
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

Efficient segmentation of the substantia nigra (SN) in midbrain cerebral images is a prerequisite for reliable quantification and evaluation of severity of Parkinson’s disease (PD). General-purpose edge-detection techniques aren’t sufficient to for accurate segmentation due to inconsistent shape and fuzzy boundaries. Additionally, the regional properties (such as grey level) of the SN and other cerebral structures are significantly similar, and thus misclassification of segmented regions is also expected. This paper presents an algorithm for localization and segmentation of the SN in neuromelanin-sensitive magnetic resonance imaging (MRI) of the midbrain. The localization is performed using a cross-correlation template matching model in which multiple templates were used to find a match with Cerebral Peduncle, a collective structure of the SN and cerebral crus in the midbrain. We adopted a new approach that uses the parametric equation of cardioid plane curve (a curve that resembles the general structure of cerebral peduncle) to generate multiple deformable templates for localization algorithm. The segmentation of the SN is then performed using the freeform active contour segmentation model in the localized region. A total of 60 slices (10 training, 50 testing), obtained from 19 scans of 10 healthy volunteers and 9 patients with PD, were acquired using a 3T MRI system. The localization algorithm succeeded in 99.8% of the cases, while the segmentation method outperformed with an average sensitivity= 0.83, specificity = 0.97, and Dice-score = 0.73.

Conference Presentation

Citation Download Citation

Touseef Ahmad Qureshi, Elliot Hogg, Cody Lynch, Debiao Li, Michele Tagliati, and Zhaoyang Fan "Substantia nigra segmentation on neuromelanin-sensitive MRI", Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109530Y (15 March 2019); https://doi.org/10.1117/12.2512909

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available