On Using Lacunarity for Diagnosis of Breast Diseases Considering Thermal Images

A experimental scheme for identification of breast diseases based on thermal images is presented. A set of infrared images from a database that is being developed were used for an experimental investigation considering the image Lacunarity measures by the gliding box algorithm. This approach generates a parameter to distinguish from normal to abnormal breast diagnostics. We propose two interpretations based in similarity of the breast anatomic aspects. The original contributions of this work are the use of thermal image on diagnosis of breast disease and an approach that classifies images based on lacunarity indexes.