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Published in:
2024 | OriginalPaper | Chapter
Preprocessing Evaluation and Benchmark for Multi-structure Segmentation of the Male Pelvis in MRI on the Gold Atlas Dataset
Authors : Francesca De Benetti, Smaranda Bogoi, Nassir Navab, Thomas Wendler
Published in: Bildverarbeitung für die Medizin 2024
Publisher: Springer Fachmedien Wiesbaden
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In radiation therapy (RTx), an accurate delineation of the regions of interest and organs at risk allows for a more targeted irradiation with reduced side effects. In the case of prostate cancer treatments, RTx planning requires the delineation of many pelvic structures. This is a time-consuming task and clinicians would greatly benefit from using robust automatic multi-structure segmentation tools.With the final purpose of introducing an automatic segmentation algorithm in clinical practice, we first address the problem of multi-structure segmentation in pelvic MR using a publicly available dataset. Moreover, we evaluate three types of preprocessing approaches to enable training and inference using different MR sequences. Despite a limited number of training samples, we report an average Dice score of 84.7 ± 10.2% in the segmentation of 8 pelvic structures. The code and the trained models are available at: https://github.com/FrancescaDB/multi_structure_segmentation_gold_atlas