A real-time patient orientation verification system using pose estimation in CT simulation

Abstract

Patient orientation mis-entry during computed tomography (CT) simulation represents a critical failure mode that corrupts the digital imaging and communications in medicine (DICOM) coordinate system, necessitating patient recall for re-scanning or complex manual corrections. We implemented a tool called just another secondary evaluation (JASE), an automated real-time verification system to prevent these errors. JASE uses a standard webcam to classify patient orientation into four standard categories: head-first-supine (HFS), head-first-prone (HFP), feet-first-supine (FFS), and feet-first-prone (FFP). We compared two approaches: transfer learning with MobileNetV2 and a multilayer perceptron (MLP) using MediaPipe pose landmarks. The system displays real-time orientation on an LCD screen adjacent to the CT console. The MLP model achieved 98.3% accuracy (1/49 misclassifications) versus 96.2% for MobileNetV2 (3/80 misclassifications) on an independent test set. Real-time implementation demonstrated stable performance, which indicates the potential for future clinical deployment pending validation in actual CT simulation workflows. JASE provides a low-cost, effective solution for preventing orientation errors at the point of entry. The system’s applicability extends beyond radiation oncology to radiology and nuclear medicine departments using similar imaging protocols.