Performance Evaluation of Color Models in the Fusion of Functional and Anatomical Images
Fusion of the functional image with an anatomical image provides additional diagnostic information. It is widely used in diagnosis, treatment planning, and follow-up of oncology. Functional image is a low-resolution pseudo color image representing the uptake of radioactive tracer that gives the impo...
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Published in | Journal of medical systems Vol. 40; no. 5; p. 122 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York
Springer US
01.05.2016
Springer Nature B.V |
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Abstract | Fusion of the functional image with an anatomical image provides additional diagnostic information. It is widely used in diagnosis, treatment planning, and follow-up of oncology. Functional image is a low-resolution pseudo color image representing the uptake of radioactive tracer that gives the important metabolic information. Whereas, anatomical image is a high-resolution gray scale image that gives structural details. Fused image should consist of all the anatomical details without any changes in the functional content. This is achieved through fusion in de-correlated color model and the choice of color model has greater impact on the fusion outcome. In the present work, suitability of different color models for functional and anatomical image fusion is studied. After converting the functional image into de-correlated color model, the achromatic component of functional image is fused with an anatomical image by using proposed nonsubsampled shearlet transform (NSST) based image fusion algorithm to get new achromatic component with all the anatomical details. This new achromatic and original chromatic channels of functional image are converted to RGB format to get fused functional and anatomical image. Fusion is performed in different color models. Different cases of SPECT-MRI images are used for this color model study. Based on visual and quantitative analysis of fused images, the best color model for the stated purpose is determined. |
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AbstractList | Fusion of the functional image with an anatomical image provides additional diagnostic information. It is widely used in diagnosis, treatment planning, and follow-up of oncology. Functional image is a low-resolution pseudo color image representing the uptake of radioactive tracer that gives the important metabolic information. Whereas, anatomical image is a high-resolution gray scale image that gives structural details. Fused image should consist of all the anatomical details without any changes in the functional content. This is achieved through fusion in de-correlated color model and the choice of color model has greater impact on the fusion outcome. In the present work, suitability of different color models for functional and anatomical image fusion is studied. After converting the functional image into de-correlated color model, the achromatic component of functional image is fused with an anatomical image by using proposed nonsubsampled shearlet transform (NSST) based image fusion algorithm to get new achromatic component with all the anatomical details. This new achromatic and original chromatic channels of functional image are converted to RGB format to get fused functional and anatomical image. Fusion is performed in different color models. Different cases of SPECT-MRI images are used for this color model study. Based on visual and quantitative analysis of fused images, the best color model for the stated purpose is determined. |
ArticleNumber | 122 |
Author | Ganasala, Padma Kumar, Vinod Prasad, A. D. |
Author_xml | – sequence: 1 givenname: Padma surname: Ganasala fullname: Ganasala, Padma email: Padma_417@yahoo.co.in organization: Department of Electrical Engineering, Indian Institute of Technology Roorkee – sequence: 2 givenname: Vinod surname: Kumar fullname: Kumar, Vinod organization: Department of Electrical Engineering, Indian Institute of Technology Roorkee – sequence: 3 givenname: A. D. surname: Prasad fullname: Prasad, A. D. organization: Department of Civil Engineering, National Institute of Technology Raipur |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27037686$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Algorithms Color Fusion Health Informatics Health Sciences Humans Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - methods Medical diagnosis Medical imaging Medicine Medicine & Public Health NMR Nuclear magnetic resonance Performance evaluation Statistics for Life Sciences Systems-Level Quality Improvement Tomography, Emission-Computed, Single-Photon - methods |
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Title | Performance Evaluation of Color Models in the Fusion of Functional and Anatomical Images |
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