Detection and characterization of abnormal vascular patterns in automated cervical image analysis

In colposcopy, mosaic and punctation are two major abnormal vessels associated with cervical intraepithelial neoplasia (CIN). Detection and characterization of mosaic and punctation in digital cervical images is a crucial step towards developing a computer-aided diagnosis (CAD) system for cervical cancer screening and diagnosis. This paper presents automated techniques for detection and characterization of mosaic and punctation vessels in cervical images. The techniques are based on iterative morphological operations with various sizes of structural elements, in combination with adaptive thresholding. Information about color, region, and shape properties is used to refine the detection results. The techniques have been applied to clinical data with promising results.