Paper Info
Title
Automated Collagen Proportional Area Extraction in Liver Biopsy Images Using a Novel Classification via Clustering Algorithm
Abstract
Diagnosis and staging of liver diseases are essential for the therapeutic efficacy of medication and treatment strategies. Measuring the Collagen Proportional Area (CPA) in liver biopsies recently becomes an effective tool for the assessment of fibrosis in liver tissues. State of the art image processing techniques are employed to analyze biopsy images, providing objective assessment of diseases severity. In current work a novel modification of K-means clustering is proposed for image segmentation of liver biopsies. More specifically, supervised restriction of centroids movement is utilized. In the first stage, a training set of images are employed to extract a hypercube for each class. Then, one centroid is initialized inside each hypercube and during the iterations of the clustering is allowed to move only inside the hypercube. For the evaluation of the proposed method 8 liver biopsy images are employed and classification results along with CPA values are computed for each image.
Year
DOI
Venue
2017
10.1109/CBMS.2017.99
2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)
Keywords
Field
DocType
collagen proportional area,liver biobsy image processing,liver fibrosis
Computer vision,Computer science,Liver biopsy,Image processing,Biopsy,Image segmentation,Artificial intelligence,Statistical classification,Cluster analysis,Hypercube,Centroid
Conference
ISSN
ISBN
Citations 
2372-9198
978-1-5386-1711-3
0
PageRank 
References 
Authors
0.34
1
7
Name
Order
Citations
PageRank
Dimosthenis C. Tsouros101.35
Panagiotis N. Smyrlis201.35
Markos G. Tsipouras337230.51
Dimitrios G. Tsalikakis4134.58
Nikolaos Giannakeas54312.59
Alexandros T. Tzallas622527.88
Pinelopi Manousou742.72