Paper
17 March 2015 MRI visualisation by digitally reconstructed radiographs
Antoine Serrurier, Andrea Bönsch, Robert Lau, Thomas M. Deserno
Author Affiliations +
Abstract
Visualising volumetric medical images such as computed tomography and magnetic resonance imaging (MRI) on picture archiving and communication systems (PACS) clients is often achieved by image browsing in sagittal, coronal or axial views or three-dimensional (3D) rendering. This latter technique requires fine thresholding for MRI. On the other hand, computing virtual radiograph images, also referred to as digitally reconstructed radiographs (DRR), provides in a single two-dimensional (2D) image a complete overview of the 3D data. It appears therefore as a powerful alternative for MRI visualisation and preview in PACS. This study describes a method to compute DRR from T1-weighted MRI. After segmentation of the background, a histogram distribution analysis is performed and each foreground MRI voxel is labeled as one of three tissues: cortical bone, also known as principal absorber of the X-rays, muscle and fat. An intensity level is attributed to each voxel according to the Hounsfield scale, linearly related to the X-ray attenuation coefficient. Each DRR pixel is computed as the accumulation of the new intensities of the MRI dataset along the corresponding X-ray. The method has been tested on 16 T1-weighted MRI sets. Anterior-posterior and lateral DRR have been computed with reasonable qualities and avoiding any manual tissue segmentations. This proof-of-concept holds for research application for use in clinical PACS.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Antoine Serrurier, Andrea Bönsch, Robert Lau, and Thomas M. Deserno "MRI visualisation by digitally reconstructed radiographs", Proc. SPIE 9418, Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, 94180I (17 March 2015); https://doi.org/10.1117/12.2081845
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Magnetic resonance imaging

Bone

Tissues

Image segmentation

Radiography

Picture Archiving and Communication System

Visualization

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