Title :
Graph-based multi-resolution segmentation of histological whole slide images
Author :
Roullier, V. ; Ta, V.-T. ; Lézoray, O. ; Elmoataz, A.
Author_Institution :
GREYC, Univ. de Caen Basse-Normandie, Caen, France
Abstract :
In this paper, we present a graph-based multi-resolution approach for mitosis extraction in breast cancer histological whole slide images. The proposed segmentation uses a multi-resolution approach which reproduces the slide examination done by a pathologist. Each resolution level is analyzed with a focus of attention resulting from a coarser resolution level analysis. At each resolution level, a spatial refinement by semi-supervised clustering is performed to obtain more accurate segmentation around edges. The proposed segmentation is fully unsupervised by using domain specific knowledge.
Keywords :
biomedical optical imaging; cancer; graph theory; image resolution; image segmentation; mammography; medical image processing; pattern clustering; breast cancer; coarser resolution level analysis; domain specific knowledge; graph-based multi-resolution segmentation; histological whole slide imaging; mitosis extraction; semi-supervised clustering; spatial refinement; Breast cancer; Decision making; Focusing; Hilbert space; Image segmentation; Lymph nodes; Medical treatment; Microscopy; Multiresolution analysis; Spatial resolution; Breast cancer; Graph; Segmentation;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location :
Rotterdam
Print_ISBN :
978-1-4244-4125-9
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2010.5490390