Publication Details
Overview
 
 
Maykel Orozco, Cosmin Mihai, Hichem Sahli, A. Taboada
 

Chapter in Book/ Report/ Conference proceeding

Abstract 

In this paper, we propose a two-phase approach to nuclei segmentation/classification in Pap smear test images. The first phase, the segmentation phase, are formed by a morphological algorithm, watershed, and a hierarchical merging algorithm, waterfall. In the merging step, waterfall uses spectral, shape information as well as the class information. In the second phase, classification, the goal is to obtain nucleus regions and cytoplasm areas by classifying the regions resulting from the first phase based on their spectral and shape features, merging of adjacent regions belonging to the same class. Between the two phases, three unsupervised segmentation quality criteria were tested in order to determine the best one selecting the best level after merging. The classification of the of individual regions is obtained using a Support Vector Machine (SVM) classifier. The segmentation/classification results are compared to segmentation provided by pathologist experts and demonstrate the efficacy of the proposed method.

Reference