Stefan Benedikt, Philipp Zelger, Lukas Horling, Kerstin Stock, Johannes Pallua, Michael Schirmer, Gerald Degenhart, Alexander Ruzicka, Rohit Arora
In vivo high-resolution peripheral quantitative computed tomography (HR-pQCT) studies on bone characteristics are limited, partly due to the lack of standardized and objective techniques to describe motion artifacts responsible for lower-quality images. This study investigates the ability of such deep-learning techniques to assess image quality in HR-pQCT datasets of human scaphoids. In total, 1451 stacks of 482 scaphoid images from 53 patients, each with up to six follow-ups within one year, and each with one non-displaced fractured and one contralateral intact scaphoid, were independently graded by three observers using a visual grading scale for motion artifacts...
March 6, 2024: Diagnostics