Basal cell carcinoma is the most abundant malignant neoplasm in humans, the pathology of which is characterized by an abnormal proliferation of basal cells. Basal cell carcinoma can show a variety of different morphologies, which are based on different cellular biology. Furthermore, the carcinoma often grows invisibly to the eye imbedded in the surrounding skin. Therefore, in some cases its clinical detection is challenging. Thus, our work aims at establishing an unsupervised tissue classification method based on multimodal imaging and the application of chemometrics to discriminate basal cell carcinoma from non-diseased tissue. A case study applying multimodal imaging to ex-vivo sections of basal cell carcinoma is presented. In doing so, we apply a combination of various linear and non-linear imaging modalities, i.e. fluorescence, Raman and second-harmonic generation microscopy, to study the morphochemistry of basal cell carcinoma. The joint information content obtained by such multimodal approach in studying various aspects of the malignant tissue alterations associated with basal cell carcinoma is discussed.