Segmentation of intervertebral disks from videofluorographic images using convolutional neural network

Ayano Fujinaka; Yuki Saito; Kojiro Mekata; Hotaka Takizawa; Hiroyuki Kudo

doi:10.1117/12.2521249

27 March 2019 Segmentation of intervertebral disks from videofluorographic images using convolutional neural network

Ayano Fujinaka, Yuki Saito, Kojiro Mekata, Hotaka Takizawa, Hiroyuki Kudo

Proceedings Volume 11050, International Forum on Medical Imaging in Asia 2019; 110501I (2019) https://doi.org/10.1117/12.2521249
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

Swallowing is achieved by a sequence of actions performed by cervical structures. Although a lot of patients suffer from dysphagia in the world, the mechanism and kinematics of swallowing are not elucidated sufficiently. This study aims to segment intervertebral disks (IDs), which are ones of representative cervical structures, in videofluorographic (VF) images by use of convolutional neural network (CNN). The proposed method consists of three steps: extraction of cervical masks, CNN-based segmentation of candidate regions of IDs, and the elimination of false positives. This segmentation method was applied to actual VF images of eleven participants that have fifty-one not-occluded IDs, and forty-three IDs were segmented successfully.

Citation Download Citation

Ayano Fujinaka, Yuki Saito, Kojiro Mekata, Hotaka Takizawa, and Hiroyuki Kudo "Segmentation of intervertebral disks from videofluorographic images using convolutional neural network", Proc. SPIE 11050, International Forum on Medical Imaging in Asia 2019, 110501I (27 March 2019); https://doi.org/10.1117/12.2521249

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