An image model and segmentation algorithm for reflection confocal images of in vivo cervical tissue

A model that accounts for the properties of the imaging system and of the tissues is developed to get a better understanding of confocal reflectance microscopy images of cervical tissues, and to supply a basis for parameter selection in a classification algorithm. The algorithm was applied to an extensive set of cervical images and it was found that it detects 90% of hand-segmented nuclei with an average of 6 false positive per frame.