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 inJournal of medical systems Vol. 40; no. 5; p. 122
Main Authors Ganasala, Padma, Kumar, Vinod, Prasad, A. D.
Format Journal Article
LanguageEnglish
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.
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.
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  surname: Ganasala
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  givenname: Vinod
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  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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StartPage 122
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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