Résumé 0

Modern medical imaging systems provide information about the patient's health condition. Their precision, resolution and sensitivity are increasing, and new possibilities of differentiating the condition of tissue are constantly appearing. These advances are also taking place in musculoskeletal imaging. Increasingly accurate imaging in various modalities allows us to discover new relationships between the image and the diagnosis. It is therefore important to use all this information to best serve the patient. That is why research related to the analysis of medical images is so important, because it allows us to indicate what is invisible to the naked eye or to quantify what has so far been measured by humans or subject to discretionary assessment. This collection includes 25 works related to the analysis of images created during diagnostics of the musculoskeletal system using various modalities—from X-ray and fluoroscopy to conventional or spectral computed tomography, magnetic resonance imaging, ultrasound, elastography, PET/CT and systems for analyzing patient mechanics. Research was carried out related to the detection of various conditions, parameterization of clinical and population phenomena, and detection of image–clinical condition relationships. Despite the current popularity of machine learning techniques, the collection is dominated by classic engineering methods related to image processing. Several works use textural analysis, which has not been appreciated so far, which is particularly related to the imaging of the structure, especially of bones.