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Authors: S. N. Jensen 1 ; R. Irani 1 ; T. B. Moeslund 1 and Christian Rankl 2

Affiliations: 1 Aalborg University, Denmark ; 2 Agilent Technologies, Austria

Keyword(s): Cell Segmentation, Microscopy Image Analysis, Object Detection, Pixel Classification.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping

Abstract: In this paper, we propose an approach for achieving generalized segmentation of microorganisms in microscopy images. It employs a pixel-wise classification strategy based on local features. Multilayer perceptrons are utilized for classification of the local features and is trained for each specific segmentation problem using supervised learning. This approach was tested on five different segmentation problems in bright field, differential interference contrast, fluorescence and laser confocal scanning microscopy. In all instance good results were achieved with the segmentation quality scoring a Dice coefficient of 0.831 or higher.

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Paper citation in several formats:
Jensen, S.; Irani, R.; Moeslund, T. and Rankl, C. (2014). General Purpose Segmentation for Microorganisms in Microscopy Images. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP; ISBN 978-989-758-003-1; ISSN 2184-4321, SciTePress, pages 690-695. DOI: 10.5220/0004827106900695

@conference{visapp14,
author={S. N. Jensen. and R. Irani. and T. B. Moeslund. and Christian Rankl.},
title={General Purpose Segmentation for Microorganisms in Microscopy Images},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP},
year={2014},
pages={690-695},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004827106900695},
isbn={978-989-758-003-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP
TI - General Purpose Segmentation for Microorganisms in Microscopy Images
SN - 978-989-758-003-1
IS - 2184-4321
AU - Jensen, S.
AU - Irani, R.
AU - Moeslund, T.
AU - Rankl, C.
PY - 2014
SP - 690
EP - 695
DO - 10.5220/0004827106900695
PB - SciTePress