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Proceedings Paper

Brain tumor segmentation using 3D mask R-CNN for dynamic susceptibility contrast enhanced perfusion imaging
Author(s): Jiwoong Jeong; Yang Lei; Hui-Kuo Shu; Tian Liu; Liya Wang; Walter Curran; Hui Mao; Xiaofeng Yang
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Paper Abstract

The detection and segmentation of neoplasms are an important part of radiotherapy treatment planning, monitoring disease progression, and predicting patient outcome. In the brain, functional magnetic resonance imaging (MRI) like dynamic susceptibility contrast enhanced (DSC) or T1-weighted dynamic contrast enhanced (DCE) perfusion MRI are important tools for diagnosis. However, the manual contouring of these neoplasms are tedious, expensive, time-consuming, and contains inter-observer variability. In this work, we propose to use a 3D Mask R-CNN method to automatically detect and segment high and low grade brain tumors for DSC MRI perfusion images. Twenty-two high and low grade patients with 50-70 perfusion time-point volumes were used in this study. Experimental results show that our proposed method achieved an overall Dice similarity, precision, recall and center of mass distance were 89%±0.03%, 90%±0.02%, 87%±0.04% and 1.27±0.67 respectively.

Paper Details

Date Published: 28 February 2020
PDF: 7 pages
Proc. SPIE 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1131720 (28 February 2020); doi: 10.1117/12.2549288
Show Author Affiliations
Jiwoong Jeong, Winship Cancer Institute, Emory Univ. (United States)
Yang Lei, Winship Cancer Institute, Emory Univ. (United States)
Hui-Kuo Shu, Winship Cancer Institute, Emory Univ. (United States)
Tian Liu, Winship Cancer Institute, Emory Univ. (United States)
Liya Wang, Winship Cancer Institute, Emory Univ. (United States)
Walter Curran, Winship Cancer Institute, Emory Univ. (United States)
Hui Mao, Winship Cancer Institute, Emory Univ. (United States)
Xiaofeng Yang, Winship Cancer Institute, Emory Univ. (United States)


Published in SPIE Proceedings Vol. 11317:
Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor S. Gimi, Editor(s)

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