Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Dong, Xiao; Lu, Huanxiang; Sakurai, Yasuo; Yamagata, Hitoshi; Zheng, Guoyan; Reyes, Mauricio (2010). Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries. In: Wang, Fei; Yan, Pingkun; Suzuki, Kenji; Shen, Dinggang (eds.) Machine learning in Medical Imaging (MLMI) - MICCAI 2010 Workshop. Lecture Notes in Computer Science: Vol. 6357 (pp. 10-17). Berlin: Springer 10.1007/978-3-642-15948-0_2

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Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.

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