Automatic evaluation of hemangiomas for follow-up monitoring

Infantile hemangiomas are the most common types of tumors with an incidence of approximately 10% in the common population. An accurate monitoring of the progress of hemangioma growth and regression is essential for an effective treatment. This study presents an automatic evaluation of the evolution of hemangioma on a follow-up series of images based on color and area features. A color constancy approach is applied to correct the variation of ambient illumination. The hemangioma segmentation uses a two-level thresholding approach with some post-processing methods. The proposed method has been tested on 25 hemangioma cases annotated by clinicians.