Image Processing

Synthesis of intensity gradient and texture information for efficient three-dimensional segmentation of medical volumes

[+] Author Affiliations
Sreenath Rao Vantaram, Yang Hu

Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, 1 Lomb Memorial Drive, Rochester, New York 14623, United States

Eli Saber, Sohail A. Dianat

Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, 1 Lomb Memorial Drive, Rochester, New York 14623, United States

Rochester Institute of Technology, Department of Electrical and Microelectronic Engineering, 1 Lomb Memorial Drive, Rochester, New York 14623, United States

J. Med. Imag. 2(2), 024003 (May 08, 2015). doi:10.1117/1.JMI.2.2.024003
History: Received December 1, 2014; Accepted April 16, 2015
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Abstract.  We propose a framework that efficiently employs intensity, gradient, and textural features for three-dimensional (3-D) segmentation of medical (MRI/CT) volumes. Our methodology commences by determining the magnitude of intensity variations across the input volume using a 3-D gradient detection scheme. The resultant gradient volume is utilized in a dynamic volume growing/formation process that is initiated in voxel locations with small gradient magnitudes and is concluded at sites with large gradient magnitudes, yielding a map comprising an initial set of partitions (or subvolumes). This partition map is combined with an entropy-based texture descriptor along with intensity and gradient attributes in a multivariate analysis-based volume merging procedure that fuses subvolumes with similar characteristics to yield a final/refined segmentation output. Additionally, a semiautomated version of the aforestated algorithm that allows a user to interactively segment a desired subvolume of interest as opposed to the entire volume is also discussed. Our approach was tested on several MRI and CT datasets and the results show favorable performance in comparison to the state-of-the-art ITK-SNAP technique.

© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Sreenath Rao Vantaram ; Eli Saber ; Sohail A. Dianat and Yang Hu
"Synthesis of intensity gradient and texture information for efficient three-dimensional segmentation of medical volumes", J. Med. Imag. 2(2), 024003 (May 08, 2015). ; http://dx.doi.org/10.1117/1.JMI.2.2.024003


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