Improving accuracy and efficiency of registration by mutual information using Sturges' Histogram Rule

Legg, Phillip A., Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884, Marshall, Andrew David ORCID: https://orcid.org/0000-0003-2789-1395 and Morgan, James E. 2007. Improving accuracy and efficiency of registration by mutual information using Sturges' Histogram Rule. Presented at: 11th Conference on Medical Image Understanding and Analysis 2007, Aberystwyth, Wales, 17-18 July 2007. Published in: Zwiggelaar, R. and Labrosse, F. eds. Proceedings of Medical Image Understanding and Analysis 2007. Cambridge: BMVA, pp. 26-30.

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Abstract

Mutual Information is a common technique for image registration in the medical domain, in particular where images of different modalities are to be registered. In this paper, we wish to demonstrate the benefits of applying a common method known in statistics as Sturges' Rule for selecting histogram bin size when computing Entropy as a part of the existing Mutual Information algorithm. Although Sturges' Rule is well known in the field of statistics it has received little attention in the Computer Vision community. By augmenting Mutual Information with Sturges' Rule, we show that this offers an improvement to both the runtime of the algorithm and also the accuracy of the registration. Our results are demonstrated on images of the eye, in particular, Fundus images and SLO (Scanning Laser Ophthalmoscopy) images.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Publisher:	BMVA
ISBN:	1901725332
Last Modified:	24 Oct 2022 10:44
URI:	https://orca.cardiff.ac.uk/id/eprint/45722

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