IEICE TRANSACTIONS on Information
Adaptive Local Thresholding for Co-Localization Detection in Multi-Channel Fluorescence Microscopic Images
Summary :
Automatic detection of immunoreactive areas in fluorescence microscopic images is becoming a key technique in the field of biology including neuroscience, although it is still challenging because of several reasons such as low signal-to-noise ratio and contrast variation within an image. In this study, we developed a new algorithm that exhaustively detects co-localized areas in multi-channel fluorescence images, where shapes of target objects may differ among channels. Different adaptive binarization thresholds for different local regions in different channels are introduced and the condition of each segment is assessed to recognize the target objects. The proposed method was applied to detect immunoreactive spots that labeled membrane receptors on dendritic spines of mouse cerebellar Purkinje cells. Our method achieved the best detection performance over five pre-existing methods.
- Publication
- IEICE TRANSACTIONS on Information Vol.E99-D No.11 pp.2851-2855
- Publication Date
- 2016/11/01
- Publicized
- 2016/07/27
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016EDL8118
- Type of Manuscript
- LETTER
- Category
- Biological Engineering
Authors
Eisuke ITO
Gunma University Graduate School of Science and Technology
Yusuke TOMARU
Gunma University Graduate School of Science and Technology
Akira IIZUKA
Gunma University Graduate School of Medicine
Hirokazu HIRAI
Gunma University Graduate School of Medicine
Tsuyoshi KATO
Gunma University Graduate School of Science and Technology
Keyword
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Eisuke ITO, Yusuke TOMARU, Akira IIZUKA, Hirokazu HIRAI, Tsuyoshi KATO, "Adaptive Local Thresholding for Co-Localization Detection in Multi-Channel Fluorescence Microscopic Images" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 11, pp. 2851-2855, November 2016, doi: 10.1587/transinf.2016EDL8118.
Abstract: Automatic detection of immunoreactive areas in fluorescence microscopic images is becoming a key technique in the field of biology including neuroscience, although it is still challenging because of several reasons such as low signal-to-noise ratio and contrast variation within an image. In this study, we developed a new algorithm that exhaustively detects co-localized areas in multi-channel fluorescence images, where shapes of target objects may differ among channels. Different adaptive binarization thresholds for different local regions in different channels are introduced and the condition of each segment is assessed to recognize the target objects. The proposed method was applied to detect immunoreactive spots that labeled membrane receptors on dendritic spines of mouse cerebellar Purkinje cells. Our method achieved the best detection performance over five pre-existing methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016EDL8118/_p
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@ARTICLE{e99-d_11_2851,
author={Eisuke ITO, Yusuke TOMARU, Akira IIZUKA, Hirokazu HIRAI, Tsuyoshi KATO, },
journal={IEICE TRANSACTIONS on Information},
title={Adaptive Local Thresholding for Co-Localization Detection in Multi-Channel Fluorescence Microscopic Images},
year={2016},
volume={E99-D},
number={11},
pages={2851-2855},
abstract={Automatic detection of immunoreactive areas in fluorescence microscopic images is becoming a key technique in the field of biology including neuroscience, although it is still challenging because of several reasons such as low signal-to-noise ratio and contrast variation within an image. In this study, we developed a new algorithm that exhaustively detects co-localized areas in multi-channel fluorescence images, where shapes of target objects may differ among channels. Different adaptive binarization thresholds for different local regions in different channels are introduced and the condition of each segment is assessed to recognize the target objects. The proposed method was applied to detect immunoreactive spots that labeled membrane receptors on dendritic spines of mouse cerebellar Purkinje cells. Our method achieved the best detection performance over five pre-existing methods.},
keywords={},
doi={10.1587/transinf.2016EDL8118},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - Adaptive Local Thresholding for Co-Localization Detection in Multi-Channel Fluorescence Microscopic Images
T2 - IEICE TRANSACTIONS on Information
SP - 2851
EP - 2855
AU - Eisuke ITO
AU - Yusuke TOMARU
AU - Akira IIZUKA
AU - Hirokazu HIRAI
AU - Tsuyoshi KATO
PY - 2016
DO - 10.1587/transinf.2016EDL8118
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2016
AB - Automatic detection of immunoreactive areas in fluorescence microscopic images is becoming a key technique in the field of biology including neuroscience, although it is still challenging because of several reasons such as low signal-to-noise ratio and contrast variation within an image. In this study, we developed a new algorithm that exhaustively detects co-localized areas in multi-channel fluorescence images, where shapes of target objects may differ among channels. Different adaptive binarization thresholds for different local regions in different channels are introduced and the condition of each segment is assessed to recognize the target objects. The proposed method was applied to detect immunoreactive spots that labeled membrane receptors on dendritic spines of mouse cerebellar Purkinje cells. Our method achieved the best detection performance over five pre-existing methods.
ER -
English
