Automated Analysis and Classification of Infected Macrophages Using Bright-Field Amplitude Contrast Data

作者：Adiga Umesh; Taylor Debbie; Bell Brian; Ponomareva Larissa; Kanzlemar Stephen; Kramer Ryan; Saldanha Roland; Nelson Sandra; Lamkin Thomas J^*

来源：Journal of Biomolecular Screening, 2012, 17(3): 401-408.

DOI：10.1177/1087057111426902

• imaging technologies
• image analysis
• high-content screening
• microscopy

This article presents a methodology for acquisition and analysis of bright-field amplitude contrast image data in high-throughput screening (HTS) for the measurement of cell density, cell viability, and classification of individual cells into phenotypic classes. We present a robust image analysis pipeline, where the original data are subjected to image standardization, image enhancement, and segmentation by region growing. This work develops new imaging and analysis techniques for cell analysis in HTS and successfully addresses a particular need for direct measurement of cell density and other features without using dyes.

• 出版日期2012-3