Multispectral Medical Image Fusion using PCA in Wavelet Domain

Moin, Aisha; Bhateja, Vikrant; Srivastava, Anuja

doi:10.1145/2905055.2905299

Cited by 6 publications

(2 citation statements)

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“… Facilitating and advancing the diagnosis through the use of functional / anatomical image fusion techniques  Increasing the planning accuracy in radiotherapy,  Allowing a quality control of radiotherapy treatment based on objective measurements [10]. Generally, the image fusion system is categorized into following approaches: image acquisition, registration, pre-processing, fusion, post-processing and deployment as presented in Figure 1.…”

Section: Medical Image Fusionmentioning

confidence: 99%

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Multimodal Brain Images Fusion using Cultural Algorithm Optimized Multispectral Features

2019

IJEAT

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Medical images can be acquired through different techniques (modalities), which have their own application areas; some of them provide information on the functional activity, while others contain only anatomic information. Usually, in the first case, images have low spatial resolution while in the second case have a higher resolution. However, the analysis of medical images often requires the evaluation of more than one modality; in order provide the specialist with more information for decision making as well as for the analysis and the treatment of diseases. Image fusion aims to combine information from the same sensor or different sensors, so that the image fused retain the information content of each individual image. In remote perception, when multispectral images are analyzed, it is very important to preserve the content of spectral information of each of the bands. The challenge is to obtain good quality images that allow us to extract as much amount of information possible, for which it is sometimes necessary to enhance or modify the image to improve its appearance or combine images or portions thereof to combine the information. An ideal fusion of multispectral images and the band panchromatic will result in a new series of bands with greater spatial resolution and equal spectral content. This paper proposes a PCA, DWT and cultural optimized entropy based DWT fusion with the evaluation parameters; arithmetic mean (SM), Maximum value ( ) and Minimum value ( ).

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Section: Medical Image Fusionmentioning

confidence: 99%

“…do the following: a. A selection of region with a window of and computed regional information entropy using equation (9) and (10).…”

Section: For Each High-frequency Sub-band Of Both Imagementioning

confidence: 99%