title: Automated tool for the detection of cell nuclei in digital microscopic images: application to retinal images.
abstract: OBJECTIVE
  To develop an automated tool that provides reliable, consistent, and accurate results for counting cell nuclei in tissue sections.
  
  
  METHODS
  We propose a novel method based on an image processing algorithm to analyze large sets of digital micrographs. The nucleus detector design is based on a Laplacian of Gaussian filter. We use the leave-one-out cross validation method for estimating the generalization error, which is then used to choose the model and parameters of the proposed nucleus detector with both fluorescent and dye stained images. We also evaluate the performance of a nucleus detector by comparing the results with manual counts.
  
  
  RESULTS
  When our nucleus detector is applied to previously unanalyzed images of feline retina, it correctly counts nuclei within the outer nuclear layer (ONL) with an average error of 3.67% ranging from 0 to 6.07%, and nuclei within the inner nuclear layer (INL) with an average error of 8.55% ranging from 0 to 13.76%. Our approach accurately identifies the location of cell bodies. Even though we have a relatively large error in the INL due to the large intra-observer variation, both manual counting and nucleus detector result in the same conclusion. This is the first time that cell death in the INL in response to retinal detachment is analyzed quantitatively. We also test the proposed tool with various images and show that it is applicable to a wide range of image types with nuclei varying in size and staining intensity.
  
  
  CONCLUSIONS
  The proposed method is simple and reliable. It also has widespread applicability to a variety of sample preparation and imaging methods. Our approach will be immediately useful in quantifying cell number in large sets of digital micrographs and from high-throughput imaging. The tool is available as a plug-in for Image J.
authors.affiliation: Department of Electrical and Computer Engineering, Center for Bio-image Informatics, University of California, Santa Barbara, CA 93106, USA. jiyun@ece.ucsb.edu
authors.forename: Jiyun
authors.initials: J
authors.lastname: Byun
authors.forename: Mark R
authors.initials: MR
authors.lastname: Verardo
authors.forename: Baris
authors.initials: B
authors.lastname: Sumengen
authors.forename: Geoffrey P
authors.initials: GP
authors.lastname: Lewis
authors.forename: B S
authors.initials: BS
authors.lastname: Manjunath
authors.forename: Steven K
authors.initials: SK
authors.lastname: Fisher
mesh_terms: D000465:Algorithms; D000818:Animals; D001331:Automation; D002415:Cats; D002467:Cell Nucleus / Q000648:ultrastructure*; D003936:Diagnosis, Computer-Assisted; D007091:Image Processing, Computer-Assisted / Q000592:standards; D008853:Microscopy; D018613:Microscopy, Confocal; D015203:Reproducibility of Results; D012160:Retina / Q000648:ultrastructure*; D012163:Retinal Detachment / Q000473:pathology