Title
Segmentation of prostatic glands in histology images
Abstract
We describe a technique for segmenting individual prostatic glands in hematoxylin-and-eosin stained prostatic tissue images. The method begins with image artifact correction, then segments the image into four tissue components using principal component analysis and k-means clustering, and finally identifies glands using a region-growing algorithm. We calculated the average gland size to distinguish cancer glands from non-cancer glands. Quantitative comparison between computer and manual outlines of glands based on 62 images (25 containing cancer) indicated an agreement of up to 67%, which approached the inter-observer agreement. Subjective evaluation corroborated these quantitative results and indicated that the technique segmented benign glands more accurately than malignant glands. Area under the receiver operating characteristic (ROC) curve of the average-gland-size feature was 0.92 in distinguishing prostate cancer from non-cancer glands.
Year
DOI
Venue
2011
10.1109/ISBI.2011.5872824
ISBI
Keywords
Field
DocType
hematoxylin-eosin stained prostatic tissue images,pattern clustering,prostate cancer,biomedical optical imaging,image segmentation,segmentation,benign glands,k-means clustering,image artifact correction,region growing algorithm,receiver operating characteristic curve,cancer glands,prostatic glands,cancer,malignant glands,computer-aided diagnosis,histologic image,histology images,tumours,principal component analysis,medical image processing,sensitivity analysis,receiver operator characteristic,k means clustering,roc curve,region growing,hematoxylin and eosin
Anatomy,Receiver operating characteristic,Pattern clustering,Computer-aided diagnosis,Image segmentation,Artificial intelligence,Prostate cancer,Medicine,Histology,Pathology,Computer vision,Segmentation,Image Artifact
Conference
ISSN
ISBN
Citations 
1945-7928 E-ISBN : 978-1-4244-4128-0
978-1-4244-4128-0
7
PageRank 
References 
Authors
0.88
4
6
Name
Order
Citations
PageRank
Yahui Peng170.88
Yulei Jiang2808.90
Laurie Eisengart370.88
Mark A. Healy4121.78
Francis H. Straus570.88
Ximing J. Yang670.88