Three dimensional reconstruction of neuron morphology from confocal microscopy images

Zian Fanti; M. Elena Martinez-Perez

doi:10.1117/12.851347

5 May 2010 Three dimensional reconstruction of neuron morphology from confocal microscopy images

Zian Fanti, M. Elena Martinez-Perez

Proceedings Volume 7723, Optics, Photonics, and Digital Technologies for Multimedia Applications; 77231E (2010) https://doi.org/10.1117/12.851347
Event: SPIE Photonics Europe, 2010, Brussels, Belgium

Abstract

In recent years it has been more common to see 3D visualization of objects applied in many different areas. In neuroscience research, 3D visualization of neurons acquired at different depth views (i.e. image stacks) by means of confocal microscopy are of increase use. However in the best case, these visualizations only help to have a qualitative description of the neuron shape. Since it is well know that neuronal function is intimately related to its morphology. Having a precise characterization of neuronal structures such as axons and dendrites is critical to perform a quantitative analysis and thus it allows to design neuronal functional models based on neuron morphology. Currently there exists different commercial software to reconstruct neuronal arbors, however these processes are labor intensive since in most of the cases they are manually made. In this paper we propose a new software capable to reconstruct 3D neurons from confocal microscopy views in a more efficient way, with minimal user intervention. The propose algorithm is based on finding the tubular structures present in the stack of images using a modify version of the minimal graph cut algorithm. The model is generated from the segmented stack with a modified version of the Marching Cubes algorithm to generate de 3D isosurface. Herein we describe the principles of our 3D segmentation technique and the preliminary results.

Citation Download Citation

Zian Fanti and M. Elena Martinez-Perez "Three dimensional reconstruction of neuron morphology from confocal microscopy images", Proc. SPIE 7723, Optics, Photonics, and Digital Technologies for Multimedia Applications, 77231E (5 May 2010); https://doi.org/10.1117/12.851347

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image segmentation

Neurons

3D modeling

Image processing

Confocal microscopy

Deconvolution

3D image processing

Show All Keywords

Keywords/Phrases

Search In:

Publication Years