We describe a method to automatically detect and label the vertebrae in human lumbar spine MRI scans. The method is based on detections in all slices of sagittal MRI scans of arbitrary slice spacing. Our contribution is to show that marrying two strong algorithms (the DPM object detector of Felzenszwalb et al. [1], and inference using dynamic programming on chains) together with appropriate modelling, results in a simple, computationally cheap procedure, that achieves stateof- the-art performance. The training of the algorithm is principled, and heuristics are not required. The method is evaluated quantitatively on a dataset of 371 MRI scans, and it is shown that the method copes with pathologies such as scoliosis, joined vertebrae, deformed vertebrae and disks, and imaging artifacts.We also demonstrate that the same method is applicable (without retraining) to CT scans.
CITATION STYLE
Lootus, M., Kadir, T., & Zisserman, A. (2014). Vertebrae detection and labelling in lumbar MR images. Lecture Notes in Computational Vision and Biomechanics, 17, 219–230. https://doi.org/10.1007/978-3-319-07269-2_19
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