Heatmap-Based Active Shape Model for Landmark Detection in Lumbar X-ray Images.

ABSTRACT: Medical staff inspect lumbar X-ray images to diagnose lumbar spine diseases, and the analysis process is currently automated using deep-learning techniques. The detection of landmarks is necessary in the automatic process of localizing the position and identifying the morphological features of the vertebrae. However, detection errors may occur owing to the noise and ambiguity of images, as well as individual variations in the shape of the lumbar vertebrae. This study proposes a method to improve the robustness of landmark detection results. This method assumes that landmarks are detected by a convolutional neural network-based two-step model consisting of Pose-Net and M-Net. The model generates a heatmap response to indicate the probable landmark positions. The proposed method then correct

SUBMITTER: Choi M 

PROVIDER: S-EPMC11811376 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature