Clinical evaluation of a full-image deep segmentation algorithm for the male pelvis on cone-beam CT and CT.

CONCLUSION: This study shows that modern deep neural networks are capable of producing clinically applicable organ segmentation for the male pelvis. The model is able to produce acceptable structures as frequently as current clinical routine. Therefore, deep neural networks can simplify the clinical workflow by offering initial segmentations. The study further shows that to retain the clinicians' personal preferences a structure review and correction is necessary for structures both created by other clinicians and deep neural networks. PMID: 31869676 [PubMed - as supplied by publisher]
Source: Radiotherapy and Oncology : journal of the European Society for Therapeutic Radiology and Oncology - Category: Radiology Authors: Tags: Radiother Oncol Source Type: research