Detection and Labeling of Lumbar Vertebral Body Using CNN in X-Ray Image

Abstract

Magnetospinography system is a device that measures non-invasively the magnetic field from the spinal cord, estimates the reconstructed current distribution around the spinal cord from the magnetic field and visualizes it. To estimate this distribution, itʼs necessary to extract the region of the spinal cord in a low dose plain X-ray image. However, since this region is extracted manually, the processing up to the estimation of this distribution isnʼt automated. As a result, these lead to high inspection cost. Therefore, we aim to automatically extract this region from a low dose plain X-ray image and conducting our research in three steps: i) detection and labeling of the vertebral body part, ii) contour extraction of the spinal vertebral body part, iii) extraction of this region. In this paper, as a first step, we propose the method to automatically detect and labeling lumbar vertebral body, intervertebral disc and sacrum from a lumbar lowdose plain X-ray image using CNN. Itʼs possible to robustly detect each part in high noise and low contrast images by devising CNN pre-processing and post-processing. The performance of the proposed method is evaluated using 60 plain X-ray images, and the results show the effectiveness of our approach with labeling precision reaching 93.3％.