Polyquant CT: direct electron and mass density reconstruction from a single polyenergetic source
| Autor: | Alessandro Perelli, Michael Davies, William H. Nailon, Jonathan H. Mason |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Electron density
Quantitative imaging Computer science Iterative method FOS: Physical sciences Electrons Computed tomography 02 engineering and technology Bone and Bones 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Image Processing Computer-Assisted 0202 electrical engineering electronic engineering information engineering Calibration medicine Humans Radiology Nuclear Medicine and imaging Segmentation Radiation treatment planning Radiological and Ultrasound Technology medicine.diagnostic_test Phantoms Imaging Attenuation Detector Reconstruction algorithm Physics - Medical Physics 3. Good health 020201 artificial intelligence & image processing Medical Physics (physics.med-ph) Tomography X-Ray Computed Algorithm Algorithms Energy (signal processing) |
| Zdroj: | Mason, J H, Perelli, A, Nailon, W H & Davies, M E 2017, ' Polyquant CT: direct electron and mass density reconstruction from a single polyenergetic source ', Physics in Medicine and Biology, vol. 62, no. 22, pp. 8739-8762 . https://doi.org/10.1088/1361-6560/aa9162 Physics in Medicine and Biology |
| ISSN: | 0031-9155 0146-6453 |
| DOI: | 10.1088/1361-6560/aa9162 |
| Popis: | Quantifying material mass and electron density from computed tomography (CT) reconstructions can be highly valuable in certain medical practices, such as radiation therapy planning. However, uniquely parameterising the X-ray attenuation in terms of mass or electron density is an ill-posed problem when a single polyenergetic source is used with a spectrally indiscriminate detector. Existing approaches to single source polyenergetic modelling often impose consistency with a physical model, such as water--bone or photoelectric--Compton decompositions, which will either require detailed prior segmentation or restrictive energy dependencies, and may require further calibration to the quantity of interest. In this work, we introduce a data centric approach to fitting the attenuation with piecewise-linear functions directly to mass or electron density, and present a segmentation-free statistical reconstruction algorithm for exploiting it, with the same order of complexity as other iterative methods. We show how this allows both higher accuracy in attenuation modelling, and demonstrate its superior quantitative imaging, with numerical chest and metal implant data, and validate it with real cone-beam CT measurements. Comment: 23 pages, 12 figures |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|