fMRI segmentation at 1.5T by clustering

Tae-Seong Kim; Deepak Khosla; Pankaj Patel; Manbir Singh

doi:10.1117/12.209698

24 May 1995 fMRI segmentation at 1.5T by clustering

Tae-Seong Kim, Deepak Khosla, Pankaj Patel, Manbir Singh

Proceedings Volume 2433, Medical Imaging 1995: Physiology and Function from Multidimensional Images; (1995) https://doi.org/10.1117/12.209698
Event: Medical Imaging 1995, 1995, San Diego, CA, United States

Abstract

A feasibility study was conducted to segment 1.5T fMRIs into gray matter and large veins using individual pixel intensity and temporal phase delay as two correlated parameters in gradient echo images. The time-course of each pixel in gradient echo images acquired during visual stimulation with a checkerboard flashing at 8Hz was correlated to the stimulation 'on'-'off' sequence to identify activated pixels. The temporal delay of each activated pixels was estimated by fitting its time-course to a reference sinusoidal function. The mean signal intensity difference of the activated pixels was computed by subtracting the average of the 'on' images from the average of the 'off' images. After replacing each activated pixel with 2D features (i.e., intensity and time-delay), a clustering method based on a K-means algorithm was employed to classify vein and tissue pixels. Good demarcation between large veins and activated gray matter was achieved with this method.

Citation Download Citation

Tae-Seong Kim, Deepak Khosla, Pankaj Patel, and Manbir Singh "fMRI segmentation at 1.5T by clustering", Proc. SPIE 2433, Medical Imaging 1995: Physiology and Function from Multidimensional Images, (24 May 1995); https://doi.org/10.1117/12.209698

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