Title :
Analysis for textural features in Nuclei of Cervical Cyto Images
Author :
Krishnaveni, K. ; Allwin, S. ; Kenny, S. Pradeep Kumar ; Mariappan, G.
Author_Institution :
Dept. of Comput. Sci., S. R. Naidu Coll., Sattur, India
Abstract :
Cervical cancer is one of the deadliest cancers that occur in women and the only way it could be curtailed is through an automated system. The sense of touch yields more information than visual and other senses. Here we have tried to exploit this concept by analyzing the textural features of cervical cyto images. The Nuclei of a Cervical cyto image possess immense textural information and can yield lot of clues about the cancer stage itself. Here we have analyzed different techniques that can be implemented to extract the various texture based features from a cervical cyto image.
Keywords :
cancer; cellular biophysics; image texture; medical image processing; cervical cancer; cervical cyto image; nuclei; textural features analysis; Cervical cancer; Computers; Feature extraction; Image segmentation; Information technology; Neodymium; Cervical Cancer; Cervical Cytology; Textural Features;
Conference_Titel :
Computational Intelligence and Computing Research (ICCIC), 2010 IEEE International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5965-0
Electronic_ISBN :
978-1-4244-5967-4
DOI :
10.1109/ICCIC.2010.5705914