Adaptive Local Thresholding for Co-Localization Detection in Multi-Channel Fluorescence Microscopic Images

Eisuke ITO  Yusuke TOMARU  Akira IIZUKA  Hirokazu HIRAI  Tsuyoshi KATO  

IEICE TRANSACTIONS on Information and Systems   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
co-localized spot detection,  co-localization analysis,  fluorescence microscopy,  image processing,  

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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.