Mutual information-based binarisation of multiple images of an object: An application in medical imaging
Journal article, 2013

A new method for image thresholding of two or more images that are acquired in different modalities or acquisition protocols is proposed. The method is based on measures from information theory and has no underlying free parameters nor does it require training or calibration. The method is based on finding an optimal set of global thresholds, one for each image, by maximising the mutual information above the thresholds while minimising the mutual information below the thresholds. Although some assumptions on the nature of images are made, no assumptions are made by the method on the intensity distributions or on the shape of the image histograms. The effectiveness of the method is demonstrated both on synthetic images and medical images from clinical practice. It is then compared against three other thresholding methods.

positron emission tomography

neurophysiology

medical image processing

brain

biomedical MRI

image segmentation

Author

Yaniv Gal

University of Queensland

Andrew Mehnert

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Imaging and Image Analysis

Stephen Rose

University of Queensland

Stuart Crozier

University of Queensland

IET Computer Vision

1751-9632 (ISSN) 1751-9640 (eISSN)

Vol. 7 3 163-169

Areas of Advance

Life Science Engineering (2010-2018)

Subject Categories

Medical Image Processing

DOI

10.1049/iet-cvi.2012.0135

More information

Latest update

2/28/2018