A template matching approach for segmenting microscopy images

Author

Chen, Cheng ; Wang, Wei ; Ozolek, John A. ; Lages, Nuno ; Altschuler, Steven J. ; Wu, Lani F. ; Rohde, Gustavo K.

Author_Institution

Dept. of Biomed. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA

fYear

2012

fDate

2-5 May 2012

Firstpage

768

Lastpage

771

Abstract

We describe a generic method for segmenting microscopy images based on supervised statistical modeling. The idea is to utilize example input segmentations to learn a statistical model of the shape and texture of the structures to be segmented. Segmentation of a test image then can be performed by maximizing the normalized cross correlation between the model and neighborhoods in the test image, followed by a final adjustment that utilizes nonrigid registration. We demonstrate the application of the method in segmenting several types of microscopy images of cells and nuclei.

Keywords

biomedical MRI; image segmentation; image texture; medical image processing; physiological models; statistical analysis; biomedical MRI; cellular biophysics; image segmentation; input segmentations; nonrigid registration; normalized cross correlation; segmenting microscopy imaging; supervised statistical modeling; template matching approach; texture; Biomedical imaging; Computational modeling; Image segmentation; Microscopy; Object segmentation; Principal component analysis; Shape; N-D image segmentation; Template matching; non-rigid registration; normalized cross-correlation;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on

Conference_Location

Barcelona

ISSN

1945-7928

Print_ISBN

978-1-4577-1857-1

Type

conf

DOI

10.1109/ISBI.2012.6235661

Filename

6235661