Back to Search
Start Over
Multi-component quantitative magnetic resonance imaging by phasor representation
- Source :
- Scientific Reports, 7, Scientific Reports, Vol 7, Iss 1, Pp 1-10 (2017), Scientific Reports 7 (2017), Scientific Reports, Scientific reports, vol 7, iss 1
- Publication Year :
- 2017
-
Abstract
- Quantitative magnetic resonance imaging (qMRI) is a versatile, non-destructive and non-invasive tool in life, material, and medical sciences. When multiple components contribute to the signal in a single pixel, however, it is difficult to quantify their individual contributions and characteristic parameters. Here we introduce the concept of phasor representation to qMRI to disentangle the signals from multiple components in imaging data. Plotting the phasors allowed for decomposition, unmixing, segmentation and quantification of our in vivo data from a plant stem, a human and mouse brain and a human prostate. In human brain images, we could identify 3 main T 2 components and 3 apparent diffusion coefficients; in human prostate 5 main contributing spectral shapes were distinguished. The presented phasor analysis is model-free, fast and accurate. Moreover, we also show that it works for undersampled data.
- Subjects :
- 0301 basic medicine
Urologic Diseases
Male
Aging
Computer science
Quantitative magnetic resonance imaging
Image Processing
Science
Biophysics
Image processing
Signal
Article
030218 nuclear medicine & medical imaging
03 medical and health sciences
Mice
0302 clinical medicine
Computer-Assisted
Component (UML)
Image Processing, Computer-Assisted
Animals
Humans
Life Science
Computer vision
Representation (mathematics)
Cancer
VLAG
Multidisciplinary
Plant Stems
business.industry
Prostate Cancer
Phasor
Neurosciences
Prostate
Brain
Pattern recognition
Image Enhancement
Decomposition
Magnetic Resonance Imaging
030104 developmental biology
Biofysica
Urological cancers Radboud Institute for Health Sciences [Radboudumc 15]
Biomedical Imaging
Medicine
Artificial intelligence
EPS
business
Algorithms
Subjects
Details
- ISSN :
- 20452322
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....aa6c6c90c3d6eebecaf65d769249ec6b