Segmenting Microscopy Images of Multi-Well Plates Based on Image Contrast

• Published in: Microscopy and microanalysis Vol. 23; no. 5; pp. 932 - 937
• Main Authors: Chen, Weiyang, Liao, Bo, Li, Weiwei, Dong, Xiangjun, Flavel, Matthew, Jois, Markandeya, Li, Guojun, Xian, Bo
• Format: Journal Article
• Language: English
• Published: New York, USA Cambridge University Press 01.10.2017; Oxford University Press
• Subjects: Aging; Bioinformatics; Biological activity; Biology; Bright plating; Caenorhabditis elegans; Experiments; Health care; Illumination; Image contrast; Image detection; Image processing; Image segmentation; Informatics; Instrumentation and Software; Methods; Microscopy; Nematodes; Software; bright field; uneven illumination; image segmentation; microscopy image; multi-well plate
• ISSN: 1431-9276; 1435-8115; 1435-8115
• DOI: 10.1017/S1431927617012375

Image segmentation is a key process in analyzing biological images. However, it is difficult to detect the differences between foreground and background when the image is unevenly illuminated. The unambiguous segmenting of multi-well plate microscopy images with various uneven illuminations is a challenging problem. Currently, no publicly available method adequately solves these various problems in bright-field multi-well plate images. Here, we propose a new method based on contrast values which removes the need for illumination correction. The presented method is effective enough to distinguish foreground and therefore a model organism (Caenorhabditis elegans) from an unevenly illuminated microscope image. In addition, the method also can solve a variety of problems caused by different uneven illumination scenarios. By applying this methodology across a wide range of multi-well plate microscopy images, we show that our approach can consistently analyze images with uneven illuminations with unparalleled accuracy and successfully solve various problems associated with uneven illumination. It can be used to process the microscopy images captured from multi-well plates and detect experimental subjects from an unevenly illuminated background.