DocumentCode
122574
Title
Fat detection algorithm for liver biopsy images
Author
Sumitpaibul, Pawesuda ; Damrongphithakkul, Anurak ; Watchareeruetai, Ukrit
Author_Institution
Dept. of Eng. & Technol., King Mongkut´s Inst. of Technol. Ladkrabang, Bangkok, Thailand
fYear
2014
fDate
19-21 March 2014
Firstpage
1
Lastpage
4
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%.
Keywords
diseases; image classification; image segmentation; liver; medical image processing; classification technique; fat blobs; fat detection algorithm; image-processing based method; input imaging; k-nearest neighbors; liver biopsy imaging; Biomedical imaging; Biopsy; Image resolution; Image segmentation; Liver; image processing; k-nearest neighbors; liver biopsy; liver fat detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Engineering Congress (iEECON), 2014 International
Conference_Location
Chonburi
Type
conf
DOI
10.1109/iEECON.2014.6925850
Filename
6925850
Link To Document