New snake algorithm to track neuronal structure in microscopy image

Author

Cheng, Jie ; Xu, Xiaoyin ; Cai, Hongmin ; Miller, Eric L. ; Wong, Stephen T C

Author_Institution

Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA

fYear

2005

fDate

13-16 Dec. 2005

Firstpage

537

Lastpage

540

Abstract

We present a new method using snake to segment elongated objects in optical microscopy image. Such objects include neuronal dendrites, which play an important role in regulating neurological function and have manifest changes in many neurodegenerative diseases, including Alzheimer´s disease and Parkinson´s disease. Based on our experience, standard gradient vector flow (GVF) snake has problem to track dendrites. The snake tends to stop too early due to the inhomogeneity of the dendrite signal. In the new method, we introduced an additional external force that aims to restart the region growing process and increase the capture range of the GVF snake. We tested the new method on real neuronal images and obtained better segmentation results. We demonstrate the performance of our method by examples.

Keywords

biomedical optical imaging; diseases; gradient methods; image segmentation; medical image processing; neurophysiology; optical microscopy; microscopy image; neurodegenerative diseases; neuronal dendrites; optical microscopy image; segmentation results; snake algorithm; standard gradient vector flow; track neuronal structure; Alzheimer´s disease; Bioinformatics; Biomedical imaging; Biomedical optical imaging; Deformable models; Image segmentation; Optical microscopy; Parkinson´s disease; Shape; Surface morphology;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Signal Processing and Communication Systems, 2005. ISPACS 2005. Proceedings of 2005 International Symposium on

Print_ISBN

0-7803-9266-3

Type

conf

DOI

10.1109/ISPACS.2005.1595465

Filename

1595465