Abstract
In this article, we describe a new image analysis software that allows rapid segmentation and separation of fluorescently stained cell nuclei using a fast ellipse detection algorithm. Detection time ranged between 1.84 and 3.14 s. Segmentation results were compared with manual evaluation. The achieved over-segmentation rate was 0.11 (0.1 double counts and 0.01 false positive detections), and the under-segmentation rate was of 0.03 over all images. We demonstrate the applicability of the proposed algorithm to automated counting of fluorescent-labeled cell nuclei and to tissue characterization. Moreover, the performance of the proposed algorithm is compared with preexisting automated image analysis techniques described by others.
MeSH terms
-
Algorithms
-
Aluminum Silicates / chemistry
-
Biocompatible Materials / chemistry
-
Bone Density Conservation Agents / pharmacology
-
Cell Count / methods*
-
Cell Culture Techniques
-
Cell Nucleus / drug effects
-
Cell Nucleus / ultrastructure*
-
Cell Proliferation / drug effects
-
Cell Size / drug effects
-
Ceramics / chemistry
-
Diphosphonates / pharmacology
-
Endothelial Cells / drug effects
-
Endothelial Cells / ultrastructure
-
False Negative Reactions
-
False Positive Reactions
-
Feasibility Studies
-
Fibroblasts / drug effects
-
Fibroblasts / ultrastructure
-
Fluorescent Dyes
-
Humans
-
Ibandronic Acid
-
Image Processing, Computer-Assisted / methods*
-
Microscopy
-
Osteogenesis / drug effects
-
Pamidronate
-
Potassium Compounds / chemistry
-
Software
-
Stem Cells / drug effects
-
Stem Cells / ultrastructure
-
Time Factors
-
Titanium / chemistry
Substances
-
Aluminum Silicates
-
Biocompatible Materials
-
Bone Density Conservation Agents
-
Diphosphonates
-
Fluorescent Dyes
-
Potassium Compounds
-
feldspar
-
Titanium
-
Pamidronate
-
Ibandronic Acid