IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Adaptive Local Thresholding for Co-Localization Detection in Multi-Channel Fluorescence Microscopic Images
Eisuke ITOYusuke TOMARUAkira IIZUKAHirokazu HIRAITsuyoshi KATO
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2016 Volume E99.D Issue 11 Pages 2851-2855


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.

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© 2016 The Institute of Electronics, Information and Communication Engineers
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