Title :
Classification Cervical Cancer Using Histology Images
Author :
Rahmadwati ; Naghdy, Golshah ; Ross, Montse ; Todd, Catherine ; Norachmawati, E.
Author_Institution :
Sch. of Electr., Comput. & Telecommun. Eng., Univ. of Wollongong, Wollongong, NSW, Australia
Abstract :
This papers reports on methodologies and outcome of a study aiming at developing robust tool to evaluate and classify histology images of cervical cancer. Using the histology images acquired from the pathology laboratories in an Indonesian hospital, this study aims to classify cervical biopsy images based on four well known discriminatory features a) the ratio of nuclei to cytoplasm b) diameter of nuclei c) shape factor and d) roundness of nuclei. In this study, the cervical histology images are classified into three categories: 1) normal, 2) pre cancer and 3) malignant. The final system will take as input a biopsy image of the image of the cervix containing the epithelium layer and provide the classification using the new automated approach, to assist the pathologist in cervical cancer diagnosis.
Keywords :
biological tissues; cancer; image classification; medical image processing; biopsy image; cervical cancer; diagnosis; epithelium layer; histology images classification; pathology laboratories; Application software; Biopsy; Cervical cancer; Computer applications; Image analysis; Neoplasms; Pathology; Robustness; Shape; Telecommunication computing; cervical cancer; classification; diagnosis; histology;
Conference_Titel :
Computer Engineering and Applications (ICCEA), 2010 Second International Conference on
Conference_Location :
Bali Island
Print_ISBN :
978-1-4244-6079-3
Electronic_ISBN :
978-1-4244-6080-9
DOI :
10.1109/ICCEA.2010.105