Pap smear cell image classification using global MPEG-7 descriptors

Abstract

Several strategies have been previously applied for classi- fying cervical cytology cells, all pursuing a nucleus seg- mentation. Sanchez sets regions [1] using a simple threshold [2], a procedure broadly adapted to different techniques: a local adaptive segmentation nuclei proce- dure [3], seed growing [4], mathematical morphology [5], a Hough transform [6], and active contours [7]. Jantzen and Dounias propose severalcellfeaturesas morphometric descriptors, including the nucleus and cytoplasm areas, nucleus / cytoplasm proportion, nucleus and cytoplasm brightnesses, smaller and larger nucleus/cytoplasm diameters, nucleus and cytoplasm roundness, nucleus and cytoplasm perimeters, nucleus position, nucleus/cytoplasm maxima and minima. Nevertheless, these morphometric characteristics require a previous accurate segmentation, hardly achieved by human intervention using commercial software such as CHAMP (Cytology and Histology Modular Analysis Package, Aarhus, Denmark) or DIMAC (Digital Image Company) [8,9]