Computer assisted diagnosis of basal cell carcinoma using Z-transform features

• A method for computer assisted diagnosis of BCC is presented.
• The method provides the pathologist a consultative opinion in evaluating specimens.
• For the first time, Fourier features are combined to form Z-transform features.
• Experiments show that the results are in agreement with the pathologist's opinion.

Detection of basal cell carcinoma tumor is of great importance for decision making in the disease treatment procedure. Visual inspection of the histopathological slides for tumor detection is laborious, time consuming and prone to inter and intra observer variability. In this paper, we have proposed an automated method for discriminating basal cell carcinoma tumor from squamous cell carcinoma tumor in skin histopathological images using Z-transform features, which were not used previously in image classification tasks. For the first time, it is shown that how two or three Fourier transform features can be combined to form one Z-transform feature. Experiments have shown that the tumor classification results obtained by our method are in reasonable agreement with the gold standards provided by expert pathologists.