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SynQuant: an automatic tool to quantify synapses from microscopy images
Author(s) -
Yizhi Wang,
Congchao Wang,
Petter Ranefall,
Gerard Joey Broussard,
Yinxue Wang,
Guilai Shi,
Boyu Lyu,
Chiung-Ting Wu,
Yue Wang,
Lin Tian,
Guoqiang Yu
Publication year - 2019
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btz760
Subject(s) - microscopy , computer science , artificial intelligence , computer vision , pathology , medicine
Synapses are essential to neural signal transmission. Therefore, quantification of synapses and related neurites from images is vital to gain insights into the underlying pathways of brain functionality and diseases. Despite the wide availability of synaptic punctum imaging data, several issues are impeding satisfactory quantification of these structures by current tools. First, the antibodies used for labeling synapses are not perfectly specific to synapses. These antibodies may exist in neurites or other cell compartments. Second, the brightness of different neurites and synaptic puncta is heterogeneous due to the variation of antibody concentration and synapse-intrinsic differences. Third, images often have low signal to noise ratio due to constraints of experiment facilities and availability of sensitive antibodies. These issues make the detection of synapses challenging and necessitates developing a new tool to easily and accurately quantify synapses.

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