Chest X-rays are fundamental in the initial health assessment; however, the diagnosis of bone pathologies, although less common, does occur and often goes unnoticed, receiving insufficient attention. Therefore, this research focuses on the detection of specific pathologies such as cervical rib and enchondroma or bone infarction, the same ones that can be detected through chest X-rays in postero-anterior (PA) projection, aiming to provide physicians with a tool to facilitate a more accurate and timely diagnosis. To achieve this, data from the Medical Image Bank of the Valencian Community (BIMCV) was utilized. Image processing was performed using Mathematical Morphology, primarily through the application of filters, where the medical image is processed both in grayscale and in binary, obtaining detection thresholds that highlight the bone structure of the possible pathology that is notified to the doctor for observation and diagnosis. The results show an average detection sensitivity and specificity greater than 96%, demonstrating the effectiveness of the developed algorithm, as confirmed by a validating orthopedic surgeon.