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Fat detection algorithm for liver biopsy images
Author(s)
Sumitpaibul, Pawesuda
Damrongphithakkul, Anurak
Watchareeruetai, Ukrit
Date Issued
October 15, 2014
Type
Conference Paper
Abstract
This paper presents an image-processing-based method for analyzing the fat proportion in liver biopsy images. Firstly, the proposed method extracts the area of candidate fat blobs, as well as the background area, from the input image. Then the features of each candidate blobs will be computed. Finally a classification technique called k-nearest neighbors is used to classify each candidate blob if it is fat. Experimental results show that the proposed method can detect fat in the liver biopsy images with the accuracy of 97.52%.
Citation
2014 International Electrical Engineering Congress Ieecon 2014, 2014