Adaptive Local Thresholding for Fluorescence Cell Micrographs
نویسندگان
چکیده
An adaptive local thresholding method for microscope based high content analysis (HCA) is proposed. Cell micrographs of HCA contain detailed objects both in and out of focus, which cannot be correctly segmented by global thresholding methods. The proposed method utilizes adaptive local neighborhood size and double thresholding, and is able to produce segmentations that conform closely to perceptually relevant structures in the original image, robust to background noise and variation. The proposed method is applied to the segmentation of mitochondria in fluorescence cell micrographs. Comparison with both hand segmentation and other global and local thresholding methods shows that the proposed method produces results of comparable quality to hand segmentation and discovers much more detailed structure than any previous thresholding methods.
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