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Medical Image Fusion Based on Wavelet Transform
Blekinge Institute of Technology, School of Computing.
2012 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

Medical image is a core step of medical diagnosis and has been diffusely applied in modern medical domain. The technology of modern medical image is more and more mature which could present images in different modes and features. Medical image fusion is the technology that could compound two mutual images into one according to certain rules to achieve clear visual effect. By observing medical fusion image, doctor could easily confirm the position of illness. According to the mutual features of CT medical image and MRI medical image, based on the technology of wavelet transform, the paper presents twp effective and applied medical image fusion methods. The first method is based on the features of certain area. The principle is to construct weighted factor and matching degree with certain related parameters to compound the area of high frequency which presents the detailed information. To the area of low frequency, principle of maximum absolute value is selected. Finally we get the fusion image by wavelet reconfiguration. By estimate of subjectivity and objectivity, the method is applied that could export excellent visual effect and good parameters. The other method is based on lifting wavelet. It decomposes the original image to area of low frequency and high frequency, and then transforms them with different fusion rules. To area of low frequency, weighted fusion is applied and to area of high frequency, rule of maximum standard deviation is chosen. Finally we get fusion image from wavelet reconstruction. By the estimate of subjectivity and objectivity, the method is an applied and excellent way that keeps the detailed information effectively and presents clear profile. At the same time, the executed time is shorter than others.

Place, publisher, year, edition, pages
2012. , 36 p.
Keyword [en]
Medical image fusion, Wavelet transform, Regional characteristics, Lifting wavelet
National Category
Computer Science
URN: urn:nbn:se:bth-4245Local ID: diva2:831574
Available from: 2015-04-22 Created: 2012-10-23 Last updated: 2015-06-30Bibliographically approved

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