以高動態範圍臨界值切割單一神經元影像的方法及其電腦可讀儲存媒體Method of Segmenting Single Neuron Images with High-Dynamic-Range Thresholds and Computer Readable Storage Medium Thereof
本發明之以高動態範圍臨界值切割單一神經元影像的方法包含(a)備置含神經元之生物組織樣本，並對含神經元之生物組織樣本進行三維成像，以得到原始三維神經影像；(b)濾除原始三維神經影像中訊號強度在第一訊號強度臨界值以下的立體像素，以得到第一經濾除影像；(c)對第一經濾除影像進行骨架追蹤，以得到第一經追蹤影像；(d)利用一方程式計算第一經追蹤影像之每一立體像素的結構重要性分數，以得到每一立體像素的第一次結構重要性分數；(e)逐漸增加訊號強度臨界值並重複步驟(b)、(c)及(d)n-1次；及(f)加總每一立體像素的第一次結構重要性分數一直到第n次結構重要性分數。
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以高動態範圍臨界值切割單一神經元影像的方法及其電腦可讀儲存媒體Method of Segmenting Single Neuron Images with High-Dynamic-Range Thresholds and Computer Readable Storage Medium Thereof
The method of segmenting single neuron images with high-dynamic-range thresholds of the present invention includes (a) preparing a biological tissue sample containing neurons and performing imaging to this sample to obtain a three-dimensional raw neuroimage; (b) deleting voxels in the three-dimensional raw neuroimage with signal intensities below a first signal intensity threshold to obtain a first thresholded image; (c) tracing the first thresholded image to obtain a first traced image; (d) calculating a structural importance score of every voxel in the first traced image to obtain a first structural importance score of every voxel; (e) gradually increasing the signal intensity threshold and repeating (b), (c) and (d) n−1 times; (f) summing up all the n structural importance scores of every voxel; (g) deleting voxels with summed structural importance score smaller than a pre-determined value from the raw image to obtain the segmented single neuron.
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