A General System for Automatic Biomedical Image Segmentation Using Intensity Neighborhoods
Joint Authors
Chen, Cheng
Ozolek, John A.
Wang, Wei
Rohde, Gustavo K.
Source
International Journal of Biomedical Imaging
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-06-23
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Image segmentation is important with applications to several problems in biology and medicine.
While extensively researched, generally, current segmentation methods perform adequately in the applications for which they were designed, but often require extensive modifications or calibrations before being used in a different application.
We describe an approach that, with few modifications, can be used in a variety of image segmentation problems.
The approach is based on a supervised learning strategy that utilizes intensity neighborhoods to assign each pixel in a test image its correct class based on training data.
We describe methods for modeling rotations and variations in scales as well as a subset selection for training the classifiers.
We show that the performance of our approach in tissue segmentation tasks in magnetic resonance and histopathology microscopy images, as well as nuclei segmentation from fluorescence microscopy images, is similar to or better than several algorithms specifically designed for each of these applications.
American Psychological Association (APA)
Chen, Cheng& Ozolek, John A.& Wang, Wei& Rohde, Gustavo K.. 2011. A General System for Automatic Biomedical Image Segmentation Using Intensity Neighborhoods. International Journal of Biomedical Imaging،Vol. 2011, no. 2011, pp.1-12.
https://search.emarefa.net/detail/BIM-484596
Modern Language Association (MLA)
Chen, Cheng…[et al.]. A General System for Automatic Biomedical Image Segmentation Using Intensity Neighborhoods. International Journal of Biomedical Imaging No. 2011 (2011), pp.1-12.
https://search.emarefa.net/detail/BIM-484596
American Medical Association (AMA)
Chen, Cheng& Ozolek, John A.& Wang, Wei& Rohde, Gustavo K.. A General System for Automatic Biomedical Image Segmentation Using Intensity Neighborhoods. International Journal of Biomedical Imaging. 2011. Vol. 2011, no. 2011, pp.1-12.
https://search.emarefa.net/detail/BIM-484596
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-484596