Deep learning-based Wilms tumor segmentation to create 3D models for surgical planning: Implementation in the clinical workflow
Abstract
Creating 3D models based on pre-operative MRI of patients with a Wilms tumor (WT) can aid surgical planning. However, creating these models requires manual delineation (segmentation) of the MRI imaging. Deep learning can automate this, but most validations of these segmentation methods are retrospective. This article prospective evaluation of a WT segmentation method in a clinical workflow aimed at creating 3D models for surgical planning.
Keywords
Wilms TumorDeep Learning Segmentation3d Surgical PlanningPediatric OncologyMri ImagingAutomated SegmentationPediatric UrologyHashtags
#WilmsTumor#DeepLearning#SurgicalPlanning#PediatricOncology#3DModelingThis article is published on an external journal. Click below to read the full text.
Read full article ↗How to cite: GlobalCastMD. Deep learning-based Wilms tumor segmentation to create 3D models for surgical planning: Implementation in the clinical workflow. GlobalCastMD Medical Library. 2026-04-25. https://origin-library.globalcastmd.com/article/11869
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