Artificial Bee Colony (ABC) based Variable Density Sampling Scheme for CS-MRI

Jagadish, Akshay Kumar and Goswami, Soumya and Saha, Pramit and Chakrabarty, Satrajit and Rajgopal, Kasi (2017) Artificial Bee Colony (ABC) based Variable Density Sampling Scheme for CS-MRI. In: IEEE Region 10 Conference (TENCON), NOV 22-25, 2016, SINGAPORE, pp. 1254-1257.

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Abstract

The self-sustained dynamics of the bee population in nature is a result of their hierarchical working culture, efficient organizing skills and unique highly developed foraging ability, which enables them to interact effectively among each other as well as with their environment. In this paper, a novel algorithm utilizing the bee's swarm intelligence, and its heuristics based on quality and quantity of food sources (nectars) is proposed to generate a variable density sampling (VDS) scheme lOr compressive sampling (CS) based fast NMI data acquisition. The algorithm uses the scout-bees for global random selection process which is further fine-tuned by employed and onlooker-bees who forage locally in the neighborhood giving prime importance to points possessing high fitness values (or high energy) usually located around the center of k-space. The algorithm introduces the concept of searching for the high quality lOod sources in annular regions, called as bins, of varying widths. Retrospective CS-MRI simulations show that the proposed k-ABC based VDS scheme performs significantly better than other sampling schemes.

Item Type:	Conference Proceedings
Publisher:	IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Additional Information:	IEEE Region 10 Conference (TENCON), SINGAPORE, NOV 22-25, 2016
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	10 Jun 2017 04:42
Last Modified:	10 Jun 2017 04:42
URI:	http://eprints.iisc.ac.in/id/eprint/57219

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