Segmenting Microscopy Images of Multi-Well Plates Based on Image Contrast
文献类型：期刊论文
| 作者 | Chen, Weiyang3; Li, Weiwei3; Dong, Xiangjun3; Liao, Bo4; Flavel, Matthew5; Jois, Markandeya5; Li, Guojun1,6; Xian, Bo2; , |
| 刊名 | MICROSCOPY AND MICROANALYSIS
 |
| 出版日期 | 2017 |
| 卷号 | 23期号:5页码:932-937 |
| 关键词 | microscopy image uneven illumination bright field multi-well plate image segmentation |
| ISSN号 | 1431-9276 |
| DOI | 10.1017/S1431927617012375 |
| 文献子类 | Article |
| 英文摘要 | 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. |
| 学科主题 | Materials Science ; Microscopy |
| WOS关键词 | C.-ELEGANS ; BIOIMAGE INFORMATICS ; QUANTIFICATION ; DATABASE ; 3D |
| 语种 | 英语 |
| WOS记录号 | WOS:000412127300006 |
| 出版者 | CAMBRIDGE UNIV PRESS |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/803]  |
| 专题 | 中国科学院上海生命科学研究院营养科学研究所 |
| 作者单位 | 1.Capital Med Univ, Sch Publ Hlth, Beijing 100086, Peoples R China; 2.Chinese Acad Sci, Collaborat Innovat Ctr Genet & Dev Biol,CAS, Max Planck Partner Inst Computat Biol,Key Lab Com, Ctr Excellence Mol Cell Sci,Shanghai Inst Biol Sc, 320 Yue Yang Rd, Shanghai 200031, Peoples R China, 3.Qilu Univ Technol, Sch Informat, Jinan 250353, Shandong, Peoples R China; 4.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Hunan, Peoples R China; 5.La Trobe Univ, Sch Life Sci, Bundoora, Vic 3083, Australia; 6.Beijing Ctr Prevent Med Res, Beijing Ctr Dis Prevent & Control, Beijing 100013, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Chen, Weiyang,Li, Weiwei,Dong, Xiangjun,et al. Segmenting Microscopy Images of Multi-Well Plates Based on Image Contrast[J]. MICROSCOPY AND MICROANALYSIS,2017,23(5):932-937. |
| APA | Chen, Weiyang.,Li, Weiwei.,Dong, Xiangjun.,Liao, Bo.,Flavel, Matthew.,...&,.(2017).Segmenting Microscopy Images of Multi-Well Plates Based on Image Contrast.MICROSCOPY AND MICROANALYSIS,23(5),932-937. |
| MLA | Chen, Weiyang,et al."Segmenting Microscopy Images of Multi-Well Plates Based on Image Contrast".MICROSCOPY AND MICROANALYSIS 23.5(2017):932-937. |
入库方式： OAI收割
来源：上海营养与健康研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。