Automatic radiography image orientation using machine learning

Mobile digital radiography receptors, known as flat panels, apart from numerous advantages create an issue of proper image orientation. Common orientation of anatomical structures in radiography images is vital in reducing pre-diagnostic processing times. Various features and machine learning methods for determining current orientation of an image are examined with the aim of determining appropriate rotation of radiographic hand images. Obtained results are analyzed and further research directions are proposed.