We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Reseach Article

Computer Aided Molecular modeling approach of H & E (Haemotoxylin & Eosin) images of Colon Cancer

by Venkata Subbaiah Kotakadi, Gaddam Susmila Aparna, D. V. R. Sai Gopal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 9
Year of Publication: 2012
Authors: Venkata Subbaiah Kotakadi, Gaddam Susmila Aparna, D. V. R. Sai Gopal
10.5120/6289-8480

Venkata Subbaiah Kotakadi, Gaddam Susmila Aparna, D. V. R. Sai Gopal . Computer Aided Molecular modeling approach of H & E (Haemotoxylin & Eosin) images of Colon Cancer. International Journal of Computer Applications. 44, 9 ( April 2012), 5-8. DOI=10.5120/6289-8480

@article{ 10.5120/6289-8480,
author = { Venkata Subbaiah Kotakadi, Gaddam Susmila Aparna, D. V. R. Sai Gopal },
title = { Computer Aided Molecular modeling approach of H & E (Haemotoxylin & Eosin) images of Colon Cancer },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 9 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number9/6289-8480/ },
doi = { 10.5120/6289-8480 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:35:04.681541+05:30
%A Venkata Subbaiah Kotakadi
%A Gaddam Susmila Aparna
%A D. V. R. Sai Gopal
%T Computer Aided Molecular modeling approach of H & E (Haemotoxylin & Eosin) images of Colon Cancer
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 9
%P 5-8
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cancer detection and classification of histopathological images is the standard clinical practice for the diagnosis and prognosis of any cancer. In this paper we present the colon cancer detection and classification of benign and malignant tumor (Nuclei) based on H & E stained histopathology and color segmentation based staining method to distinguish the different types of tissues in biomedical application. Nucleus detection in H&E is a challenging problem considering the variability, heterogeneity, low contrast, K means clustering, and differing typologies of nuclei to distinguish different types of tissues. There are strong indications that morphological analysis in H&E can serve as a biomarker. The segmentation approach is completely colour based and uses k-means clustering technique. This technique uses a series of algorithm steps which is an image processing approach in distinguishing the different tissue types. These algorithm steps are modelled in image processing tool box of MATLAB v7. 0. Modelling steps involved are from reading the image to segmentation of the nuclei into a separate image. Further there are also the intermediate steps that are involved between reading the image and segment the nuclei into a separate image in MATLAB real-time simulation environment.

References
  1. Itzkowitz,S. H. et al. (2004) Inflammation and cancer IV. Colorectal cancer in inflammatory bowel disease: the role of inflammation. Am. J. Physiol. Gastrointest. Liver Physiol. , 287, G7–G17.
  2. Otsu Nobuyuki, "A Threshold Selection Method from gray level Histograms", vol. SMC-9, no. 1, January 1979
  3. I. Pitas, A. N. Venetsanopoulos, (1990) "Nonlinear Digital Filters
  4. Gonzalez R. C. , Woods R. E. , (1993) "Digital Image Processing",
  5. Pratt W. K. , (1991) "Digital Image Processing",
  6. G. Deng, L. W. Cahill and G. R. Tobin, "The Study of Logarithmic Image Processing Model and Its Application to Image Enhancement"
  7. Joongho Chang, Gunhee Han, Hose M. Valverde, Norman C. Grisworld, J. Francisco Duque-Carillo, Edgar anchez-Sinencio,( 1997) "Cork Quality Classification System using a Unified Image Processing and Fuzzy-Neural Network Methodology", vol. 8, no. 4, July [8 ] Crabb D. P. , Edgar D. F. , Fitzke F. W. , Mcnaught A. I. & Wynn H. P. (1995). New Approach to Estimating Variability in Visual-Field Data Using An Image-Processing Technique. British Journal of Ophthalmology 79:213-217.
Index Terms

Computer Science
Information Sciences

Keywords

Histopathology And Colon Cancer K Means Clustering color Segmentation Image Processing