Automatic Identification of Shot Body Region from Clinical Photographies

Administration of clinical photographs taken by commonly used digital camera often requires troublesome manual operation. In this paper, we made a prototype scheme of automatic photographed area identification from clinical images to help or reduce administration task. A total of 8047 clinical photographs taken in department of dermatology, Keio University Hospital, were classified into 11 categories; head, hair, upper limb, lower limb, trunk, palm, sole, back of hand, back of foot, finger & detent and genital; to meet request by several dermatologists and we developed separate linear classifiers for each body region. The developed classifiers achieved an 82.8% in sensitivity (SE) and an 82.0% of specificity (SP) in average. In addition, integration of these classifiers with consideration of the feature space of each body region improved SP of 2.3% and precision (PR) of 3.0% at a maximum when the classification threshold was set to around 75% in SE. The proposed scheme requires only photographs to identify the photographed area and therefore it can be easily applied for DICOM (digital image and communication in medicine) system that is commonly used in clinical practice or other medical database systems.