Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images

Background: Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method selection and thus more accurate results, relatively few studies have been performed. Results: To better understand algorithm performance under different conditions, we have carried out a comparative study including eleven spot detection or segmentation algorithms from various application fields. We used microscope images from well plate experiments with a human osteosarcoma cell line and frames from image stacks of yeast cells in different focal planes. These experimentally derived images permit a comparison of method performance in realistic situations where the number of objects varies within image set. We also used simulated microscope...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Pekka Ruusuvuori, Tarmo Äijö, Sharif Chowdhury, Cecilia Garmendia-Torres, Jyrki Selinummi, Mirko Birbaumer, Aimée M. Dudley, Lucas Pelkmans, Olli Yli-Harja
• Keywords: Algorithms, BMCBI 2010, Image, Microscope Images