Automatic segmentation of digital micrographs: a survey.
Digital micrographs and play a crucial role in today's bio-medical research. Due to progresses in experiment standardization and automation large sets of digital microscopy images, so called micrographs are recorded and stored to databases. The subsequent analysis of the large number of digital images needs the image information to be transformed into quantitative data, which can be processed by statistical methods and datamining. This article summarizes applications of optical microscopy in biomedical research and describes the individual characteristics in micrograph segmentation and classification. An overview on past works based on image processing and artificial neural networks is given and the problem of segmentation evaluation. It concludes with recommendations for future works.
Nattkemper
Tim W
TW
Applied Neuroinformatics Group, Faculty of Technology, Bielefeld University, Germany. tnattkem@techfak.uni-bielefeld.de
D007091:Image Processing, Computer-Assisted; D008853:Microscopy; D016571:Neural Networks, Computer; D012372:ROC Curve; D015203:Reproducibility of Results