Three-Dimensional Semantic Segmentation of Pituitary Adenomas Based on the Deep Learning Framework-nnU-Net: A Clinical Perspective

Abstract

Both nnU-Net models showed good segmentation performance for PAs > 1000 mm³ (75% of the dataset) and limited performance for PAs < 1000 mm³ (25% of the dataset). Model 2 trained with fewer samples was more cost-effective. We propose to combine the use of model-based segmentation for PA > 1000 mm³ and manual segmentation for PA < 1000 mm³ in clinical practice at the current stage.