Computer vision and image processing

Mason, Scott

doi:10.1016/0924-2716(93)90037-n

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Identification Of Cells1

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2014

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“…In the grayscale image, every pixel was represented by an intensity value ranging from 0 to 255. The image was then processed by applying two basic morphological operations, namely dilation and erosion [25]. The concept of the dilation operation was to increase the area of bright regions in the image as the erosion was to increase the area of dark regions in the image.…”

Section: Identification Of Cellsmentioning

confidence: 99%

Cell segmentation and pipette identification for automated patch clamp recording

et al. 2014

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A visual-based approach for identifying living cells and performing the automated patch clamp recording was reported. Based on the image processing and blob detection algorithm, the vision-based method was developed for the detection and identification of biological cells and micropipette. The method was implemented in a micromanipulation system that enabled the identification of the boundary and the center of the target cell and separation from its neighboring cells. The method successfully identified a batch of neuroblastoma cells with the highest yield of 90%. The results demonstrated that the visual-based approach can be integrated to the micromanipulation system to automatically manipulate the patch pipette tip to the center of the target cell, and as a result, the whole-cell recording can be performed precisely and effectively.

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Section: Identification Of Cellsmentioning

confidence: 99%