Title :
Object recognition in the ovary: Quantification of oocytes from microscopic images
Author :
Skodras, Angelos ; Giannarou, Stamatia ; Fenwick, Mark ; Franks, Stephen ; Stark, Jaroslav ; Hardy, Kate
Author_Institution :
Inst. of Reproductive & Dev. Biol., Hammersmith Hosp., London, UK
Abstract :
The ovary is a female organthat houses a fixed supply of germ cells (oocytes). The absolute number of oocytes at any given stage can be a useful indicator of fertility. Obtaining accurate assessments of the oocyte reserve in humans and experimental models can be time consuming and error prone. In this paper a new approach to facilitate oocyte counting in microscope images of mouse ovariesis presented. The mouse vasa homolog (MVH), an oocyte-specific protein, was labeled in microscope sections and used to develop an algorithm that can identify, count and estimate the size and coordinates of the oocytes. We use this automated approach to generate comparable data with conventional methods of oocyte counting.
Keywords :
biological organs; biomedical optical imaging; cellular biophysics; gynaecology; image recognition; image segmentation; medical image processing; object recognition; optical microscopy; proteins; automated approach; biological organ; brightfield light microscopy; fertility indicator; germ cells; image segmentation; light micrograph; light microscopic images; mouse ovaries; mouse vasa homolog; object recognition; oocyte coordinates size estimation; oocyte quantification; oocyte-specific protein; oocytes; Brain modeling; Gaussian noise; Image reconstruction; Magnetic resonance imaging; Microscopy; Object recognition; Rician channels; Sensor phenomena and characterization; Signal to noise ratio; Testing; follicle; image segmentation; microscope image processing; oocyte; ovary;
Conference_Titel :
Digital Signal Processing, 2009 16th International Conference on
Conference_Location :
Santorini-Hellas
Print_ISBN :
978-1-4244-3297-4
Electronic_ISBN :
978-1-4244-3298-1
DOI :
10.1109/ICDSP.2009.5201188