Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/176630
Title: | Automated detection of lupus white matter lesions in MRI |
Author: | Roura, Eloy Sarbu, Nicolae Oliver, Arnau Valverde, Sergi González Villà, Sandra Cervera i Segura, Ricard, 1960- Bargalló Alabart, Núria Lladó, Xavier |
Keywords: | Ressonància magnètica Lupus Magnetic resonance Lupus |
Issue Date: | 12-Aug-2016 |
Publisher: | Frontiers Media |
Abstract: | Brain magnetic resonance imaging provides detailed information which can be used to detect and segment white matter lesions (WML). In this work we propose an approach to automatically segment WML in Lupus patients by using T1w and fluid-attenuated inversion recovery (FLAIR) images. Lupus WML appear as small focal abnormal tissue observed as hyperintensities in the FLAIR images. The quantification of these WML is a key factor for the stratification of lupus patients and therefore both lesion detection and segmentation play an important role. In our approach, the T1w image is first used to classify the three main tissues of the brain, white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF), while the FLAIR image is then used to detect focal WML as outliers of its GM intensity distribution. A set of post-processing steps based on lesion size, tissue neighborhood, and location are used to refine the lesion candidates. The proposal is evaluated on 20 patients, presenting qualitative, and quantitative results in terms of precision and sensitivity of lesion detection [True Positive Rate (62%) and Positive Prediction Value (80%), respectively] as well as segmentation accuracy [Dice Similarity Coefficient (72%)]. Obtained results illustrate the validity of the approach to automatically detect and segment lupus lesions. Besides, our approach is publicly available as a SPM8/12 toolbox extension with a simple parameter configuration. |
Note: | Reproducció del document publicat a: https://doi.org/10.3389/fninf.2016.00033 |
It is part of: | Frontiers in Neuroinformatics, 2016, vol. 10, num. 33 |
URI: | http://hdl.handle.net/2445/176630 |
Related resource: | https://doi.org/10.3389/fninf.2016.00033 |
ISSN: | 1662-5196 |
Appears in Collections: | Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer) Articles publicats en revistes (Medicina) |
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