Automatic lumbar spine measurement in CT images

Yunxiang Mao; Dong Zheng; Shu Liao; Zhigang Peng; Ruyi Yan; Junhua Liu; Zhongxing Dong; Liyan Gong; Xiang Sean Zhou; Yiqiang Zhan; Jun Fei

doi:10.1117/12.2254460

3 March 2017 Automatic lumbar spine measurement in CT images

Yunxiang Mao, Dong Zheng, Shu Liao, Zhigang Peng, Ruyi Yan, Junhua Liu, Zhongxing Dong, Liyan Gong, Xiang Sean Zhou, Yiqiang Zhan, Jun Fei

Author Affiliations +

Proceedings Volume 10134, Medical Imaging 2017: Computer-Aided Diagnosis; 1013446 (2017) https://doi.org/10.1117/12.2254460
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Accurate lumbar spine measurement in CT images provides an essential way for quantitative spinal diseases analysis such as spondylolisthesis and scoliosis. In today’s clinical workflow, the measurements are manually performed by radiologists and surgeons, which is time consuming and irreproducible. Therefore, automatic and accurate lumbar spine measurement algorithm becomes highly desirable. In this study, we propose a method to automatically calculate five different lumbar spine measurements in CT images. There are three main stages of the proposed method: First, a learning based spine labeling method, which integrates both the image appearance and spine geometry information, is used to detect lumbar and sacrum vertebrae in CT images. Then, a multiatlases based image segmentation method is used to segment each lumbar vertebra and the sacrum based on the detection result. Finally, measurements are derived from the segmentation result of each vertebra. Our method has been evaluated on 138 spinal CT scans to automatically calculate five widely used clinical spine measurements. Experimental results show that our method can achieve more than 90% success rates across all the measurements. Our method also significantly improves the measurement efficiency compared to manual measurements. Besides benefiting the routine clinical diagnosis of spinal diseases, our method also enables the large scale data analytics for scientific and clinical researches.

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Yunxiang Mao, Dong Zheng, Shu Liao, Zhigang Peng, Ruyi Yan, Junhua Liu, Zhongxing Dong, Liyan Gong, Xiang Sean Zhou, Yiqiang Zhan, and Jun Fei "Automatic lumbar spine measurement in CT images", Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 1013446 (3 March 2017); https://doi.org/10.1117/12.2254460

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KEYWORDS

Spine

Image segmentation

Computed tomography

Sensors

Detection and tracking algorithms

Bone

Minerals

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