Challenges in Using Deep Neural Networks Across Multiple Readers in Delineating Prostate Gland Anatomy.

ABSTRACT: Deep learning methods provide enormous promise in automating manually intense tasks such as medical image segmentation and provide workflow assistance to clinical experts. Deep neural networks (DNN) require a significant amount of training examples and a variety of expert opinions to capture the nuances and the context, a challenging proposition in oncological studies (H. Wang et al., Nature, vol. 620, no. 7972, pp. 47-60, Aug 2023). Inter-reader variability among clinical experts is a real-world problem that severely impacts the generalization of DNN reproducibility. This study proposes quantifying the variability in DNN performance using expert opinions and exploring strategies to train the network and adapt between expert opinions. We address the inter-reader variability problem in the

SUBMITTER: Abudalou S 

PROVIDER: S-EPMC12921062 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature