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高通量显微镜(HTM)法自动计数空气中的石棉纤维。

Automated counting of airborne asbestos fibers by a high-throughput microscopy (HTM) method.

机构信息

Department of Mechanical Engineering, Graduate School, Kookmin University, Seoul 136-702, Korea.

出版信息

Sensors (Basel). 2011;11(7):7231-42. doi: 10.3390/s110707231. Epub 2011 Jul 18.

Abstract

Inhalation of airborne asbestos causes serious health problems such as lung cancer and malignant mesothelioma. The phase-contrast microscopy (PCM) method has been widely used for estimating airborne asbestos concentrations because it does not require complicated processes or high-priced equipment. However, the PCM method is time-consuming and laborious as it is manually performed off-site by an expert. We have developed a high-throughput microscopy (HTM) method that can detect fibers distinguishable from other spherical particles in a sample slide by image processing both automatically and quantitatively. A set of parameters for processing and analysis of asbestos fiber images was adjusted for standard asbestos samples with known concentrations. We analyzed sample slides containing airborne asbestos fibers collected at 11 different workplaces following PCM and HTM methods, and found a reasonably good agreement in the asbestos concentration. Image acquisition synchronized with the movement of the robotic sample stages followed by an automated batch processing of a stack of sample images enabled us to count asbestos fibers with greatly reduced time and labors. HTM should be a potential alternative to conventional PCM, moving a step closer to realization of on-site monitoring of asbestos fibers in air.

摘要

吸入空气中的石棉会导致严重的健康问题,如肺癌和恶性间皮瘤。相衬显微镜(PCM)方法已被广泛用于估计空气中石棉浓度,因为它不需要复杂的过程或昂贵的设备。然而,由于 PCM 方法是由专家在现场进行的,因此既耗时又费力。我们已经开发出一种高通量显微镜(HTM)方法,该方法可以通过图像处理自动且定量地检测样品载玻片上与其他球形颗粒区分开来的纤维。针对具有已知浓度的标准石棉样品,调整了用于处理和分析石棉纤维图像的一组参数。我们分析了通过 PCM 和 HTM 方法收集的 11 个不同工作场所空气中石棉纤维的样品载玻片,发现石棉浓度具有相当好的一致性。与机器人样品台的运动同步进行的图像采集,以及对一堆样品图像的自动批量处理,使我们能够大大减少时间和劳动力来计数石棉纤维。HTM 应该是传统 PCM 的潜在替代品,朝着实现空气中石棉纤维的现场监测又迈进了一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc35/3231659/13d4db1c77a5/sensors-11-07231f1.jpg

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