Evaluation of Symmetry Enhanced Sliding Band Filter for Plant Cell Nuclei Detection in Low Contrast Noisy Fluorescent Images

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

Monica Marcuzzo (Author) Other; Pedro Quelhas (Author) Other; Ana Maria Mendonca (Author) FEUP; Aurelio Campilho (Author) FEUP

Conference proceedings International

Title: Image Analysis and Recognition

Pages: 824-831

6th International Conference, ICIAR 2009

Halifax, Canada, July 6-8, 2009

Indexing

ISI Proceedings

ISI Web of Knowledge - 7 Citations

Scopus - 8 Citations

INSPEC

COMPENDEX

Scientific classification

FOS: Natural sciences > Computer and information sciences

CORDIS: Technological sciences > Engineering > Biomedical enginnering

Other information

Authenticus ID: P-003-QHN

DOI: 10.1007/978-3-642-02611-9_81

Abstract (EN): The study of cell nuclei is fundamental for plant cell Biology research. To obtain information at; cellular level, researchers image cells' nuclei which were modified with fluorescence proteins, through laser scanning confocal microscopy. These images are normally noisy and suffer from high background fluorescence, making grey-scale segmentation approaches inadequate for a usable detection. To obtain a successful detection even at low contrast we investigate the use of a particular convergence filter, the Symmetric Sliding Band filter (SSBF), for cell detection. This filter is based on gradient convergence and not intensity. As such it can detect low contrast cell nuclei which otherwise would be lost in the background noise. Due to the characteristics of cell nuclei morphology, a symmetry constrain is integrated in the filter which corrects some inadequate detections and results in a filter response that is more discriminative. We evaluate the use of this filter for cell nuclei detection on the Arabidopsis thaliana root tip, where the nuclei were stained using yellow fluorescence protein. The resulting cell nuclei detection precision is 89%.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8