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Proceedings Paper

Automatic brain arteriovenous malformations segmentation on contrast CT images using combined region proposal network and V-Net
Author(s): Yabo Fu; Yang Lei; Tonghe Wang; Xiaojun Jiang; Walter J. Curran; Tian Liu; Hui-kuo Shu; Xiaofeng Yang
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Paper Abstract

Stereotactic radiosurgery (SRS) is widely used to obliterate arteriovenous malformations (AVMs). Its performance relies on the accuracy of delineating the target AVM. Manual segmentation during a framed SRS procedure is timeconsuming and subject to inter- and intra-observer variation. Therefore, it is important to develop an automatic segmentation method to delineate the AVM target from CT images. In this study, we retrospectively investigated 80 patients who were treated with SRS. Ground truth was manually generated by an experienced physician using both DSA and CT images. A fast region proposal network was first trained to propose a bounding box that contains the AVM lesion for detection. The bounding box was then used to guide image patch sampling process for V-Net training. In the testing stage, possible AVM locations were first proposed by the region proposal network. Subsequently, V-Net was used for the final label prediction. Both the region proposal network and V-Net were trained using 60 patients and tested using 20 patients. The mean Dice similarity coefficient (DSC) was calculated to evaluate the accuracy of the proposed method. The automatic contours were in very good agreement to the ground truth contours with an average DSC < 0.85.

Paper Details

Date Published: 16 March 2020
PDF: 6 pages
Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 113142Y (16 March 2020); doi: 10.1117/12.2550385
Show Author Affiliations
Yabo Fu, Emory Univ. (United States)
Yang Lei, Emory Univ. (United States)
Tonghe Wang, Emory Univ. (United States)
Xiaojun Jiang, Emory Univ. (United States)
Walter J. Curran, Emory Univ. (United States)
Tian Liu, Emory Univ. (United States)
Hui-kuo Shu, Emory Univ. (United States)
Xiaofeng Yang, Emory Univ. (United States)

Published in SPIE Proceedings Vol. 11314:
Medical Imaging 2020: Computer-Aided Diagnosis
Horst K. Hahn; Maciej A. Mazurowski, Editor(s)

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