Quantitative Analysis of Histopathological Features of Precancerous Lesion and Condition Using Image Processing Technique

This paper aims at quantitative analysis of histopathological features of precancerous lesion and condition using image processing technique. The algorithm involves median and low pass filtering, segmentation by adaptive region growing, optimal and local thresholding, morphological operations such a...

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Published in19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06) pp. 231 - 236
Main Authors Jadhav, A.S., Banerjee, S., Dutta, P.K., Paul, R.R., Pal, M., Banerjee, P., Chaudhuri, K., Chatterjee, J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2006
Subjects
Adaptive filters
Cancer
Filtering algorithms
Image analysis
Image processing
Image segmentation
Lesions
Low pass filters
MATLAB
Morphological operations
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Summary:This paper aims at quantitative analysis of histopathological features of precancerous lesion and condition using image processing technique. The algorithm involves median and low pass filtering, segmentation by adaptive region growing, optimal and local thresholding, morphological operations such as opening and closing of gray scale and binary images and some numerical methods. Differentiation on the basis of type and level of precancerous type or condition is carried out based on image marker, defined as a vector of cancer related features viz. length and curvature of radius of rete-ridges and papillae, population density of cells within epithelium, etc. Implementation of presented algorithms is done in MATLAB. The results support quantitative analysis of pathological condition in respect with progression towards malignancy. This analysis may help in developing automated analysis tool
ISBN:9780769525174
0769525172
ISSN:1063-7125
DOI:10.1109/CBMS.2006.137