Assessing an Automated Noncontrast CT-based Pipeline for Sacral Tumor Classification Using a Hip Bone Reference Frame.

ABSTRACT: Purpose To develop a fully automated hybrid approach to predict sacral tumor types from preoperative noncontrast CT (NCCT ) images. Materials and Methods In this retrospective, multicenter study, scans were available in 690 patients who had histopathologically confirmed preoperative sacral NCCT performed between January 2011 and May 2024. A fully automated hybrid model integrated two deep convolutional neural network models (model 1 and model 2) through a fully automated pipeline. Model 1 segments tumors and hip bones automatically from NCCT images, producing masks that are used by model 2. For the first time, the hip bone was used as a reference frame for tumor localization. The second model, CL-MedImageNet, is an innovative six-classification model that allows the simultaneous input of t

SUBMITTER: Zheng F 

PROVIDER: S-EPMC12862476 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature