Selection of density standard and X-ray tube settings for computed digital absorptiometry in horses using the k-means clustering algorithm.

ABSTRACT:

Background

In veterinary medicine, conventional radiography is the first-choice method for most diagnostic imaging applications in both small animal and equine practice. One direction in its development is the integration of bone density evaluation and artificial intelligence-assisted clinical decision-making, which is expected to enhance and streamline veterinarians' daily practices. One such decision-support method is k-means clustering, a machine learning and data mining technique that can be used clinically to classify radiographic signs into healthy or affected clusters. The study aims to investigate whether the k-means clustering algorithm can differentiate cortical and trabecular bone in both healthy and affected horse limbs. Therefore, identifying the optimal computed digit

SUBMITTER: Turek B 

PROVIDER: S-EPMC11905476 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature