On Efficient Extraction of Pelvis Region from CT Data
Channel: BVM Conference
Date: 12/03/2021

The first step in automated analysis of medical volumetric data is to detect slices, where specic body parts are located. In our project, we aimed to extract the pelvis regionfrom whole-body CT scans. Two deep learning approaches, namely, an unsupervised slice score regressor, and a supervised slice classication method, were evaluated on a relatively small-sized dataset. The result comparison showed that both methods could detect the region of interest with accuracy above 93%. Although the straightforward classication method delivered more accurate results (accuracy of 99%), sometimes it tended to output discontinuous regions, which can be solved by combination of both approaches.

References:
Ivanovska T., Paulus A.O., Martin R., Panahi B., Schilling A. (2021) On Efficient Extraction of Pelvis Region from CT Data. In: Palm C., Deserno T.M., Handels H., Maier A., Maier-Hein K., Tolxdorff T. (eds) Bildverarbeitung für die Medizin 2021. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-33198-6_65