Title :
Active segmentation of 3D axonal images
Author :
Muralidhar, G.S. ; Gopinath, Anand ; Bovik, Alan C. ; Ben-Yakar, Adela
Author_Institution :
Univ. of Texas at Austin, Austin, TX, USA
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
We present an active contour framework for segmenting neuronal axons on 3D confocal microscopy data. Our work is motivated by the need to conduct high throughput experiments involving microfluidic devices and femtosecond lasers to study the genetic mechanisms behind nerve regeneration and repair. While most of the applications for active contours have focused on segmenting closed regions in 2D medical and natural images, there haven´t been many applications that have focused on segmenting open-ended curvilinear structures in 2D or higher dimensions. The active contour framework we present here ties together a well known 2D active contour model [5] along with the physics of projection imaging geometry to yield a segmented axon in 3D. Qualitative results illustrate the promise of our approach for segmenting neruonal axons on 3D confocal microscopy data.
Keywords :
biological techniques; biology computing; cellular biophysics; computer vision; image segmentation; neurophysiology; optical microscopy; 2D active contour model; 3D axonal image active segmentation; 3D confocal microscopy data; active contour framework; femtosecond lasers; genetic mechanisms; high throughput experiments; microfluidic devices; nerve regeneration; nerve repair; neuronal axon segmentation; open ended curvilinear structures; projection imaging geometry; Active contours; Image segmentation; Microscopy; Nerve fibers; Trajectory; Vectors; Animals; Axons; Caenorhabditis elegans; Imaging, Three-Dimensional; Microscopy, Confocal;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346845