The segmentation and visualization of a neuron in the housefly's visual system.
Those studying biological systems are often interested in the morphology of the various microscopic organelles. The three dimensional reconstruction and visualization of objects provide a powerful tool to understand the nature of each object, and its relationship to other objects. Segmentation is the key to 3D analysis and study of objects that have been recorded with a series of sectioned images, such as from a confocal laser scanning microscope (CLSM). Segmentation is the process of completely separating or isolating the individual objects in an image. A seed-based semi-automatic segmentation tool has been developed to aid in the process of 3D visualization of objects recorded with serial sectioned images, including a boundary creation method that maintains the separate identity of contacting objects. This segmentation tool also allows the user to retain background information as a separate object, providing important reference and landmark information for the object of interest. This paper summarizes the main parts of the segmentation algorithm and presents 3D reconstructions of visual neurons of the housefly, Musca domestica. These reconstructions are compared to typical 3D images produced from other widely used software packages, including standard CLSM imaging software and the popular ImageJ supported by National Institute of Health (NIH). Efforts are underway to develop a user-friendly graphical user interface (GUI) for the segmentation algorithm to entice broader used in research settings.
Anderson
Jeffrey R
JR
University of Wyoming, Laramie, Wyoming, USA.
Barrett
Steven F
SF
Wilcox
Michael J
MJ
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003196:Computer Graphics; D006793:Houseflies / Q000166:cytology*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D017956:Photoreceptor Cells, Invertebrate / Q000166:cytology*; D012815:Signal Processing, Computer-Assisted; D012984:Software; D014584:User-Computer Interface