In this paper, we describe a recognition method of lung nodule shadows in X-ray CT images using 3-dimensional nodule and blood vessel models. From these 3D object models, artificial CT images are generated as templates. The templates are then applied to input images which comprise of suspicious shadows. If any parameters of the suspicious shadow matches a nodule template rather than any blood vessel template, then it is determined to be abnormal. Otherwise, it is determined to be normal. By applying our new method to the actual lung CT images of 38 patients, the false positive ratio is reduced to 4.31 [shadow/patient] with the sensitivity exceeding 95%.
Novel use of the endobronchial ultrasound through esophagus (EUS-B): Diagnosis of thyroid lesions