工作流程
计算机科学
流式细胞术
样品(材料)
流量(数学)
细胞仪
校准
再现性
数据挖掘
人工智能
计算机视觉
统计
数学
生物
数据库
化学
遗传学
色谱法
几何学
作者
Viktor Jónás,Róbert Paulik,Miklós Kozlovszky,Béla Molnár
出处
期刊:Sensors
[Multidisciplinary Digital Publishing Institute]
日期:2022-09-14
卷期号:22 (18): 6952-6952
被引量:4
摘要
Ploidy analysis is the fundamental method of measuring DNA content. For decades, the principal way of conducting ploidy analysis was through flow cytometry. A flow cytometer is a specialized tool for analyzing cells in a solution. This is convenient in laboratory environments, but prohibits measurement reproducibility and the complete detachment of sample preparation from data acquisition and analysis, which seems to have become paramount with the constant decrease in the number of pathologists per capita all over the globe. As more open computer-aided systems emerge in medicine, the demand for overcoming these shortcomings, and opening access to even more (and more flexible) options, has also emerged. Image-based analysis systems can provide an alternative to these types of workloads, placing the abovementioned problems in a different light. Flow cytometry data can be used as a reference for calibrating an image-based system. This article aims to show an approach to constructing an image-based solution for ploidy analysis, take measurements for a basic comparison of the data produced by the two methods, and produce a workflow with the ultimate goal of calibrating the image-based system.
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