Paper
21 May 2001 New approach to diagnosis of pulmonary embolism using multislice CT
Matthias U. Niethammer, Uwe Joseph Schoepf, Hoachim E. Wildberger, Ernst Klotz, Heinz Fichte, Stefan Schaller
Author Affiliations +
Abstract
Suspected pulmonary embolism (PE) is a common indication for CT scanning of the thorax. Usually, intravenous contrast agent is administered utilizing a power-injector and the vascular structures are examined for the presence of pulmonary emboli. Current Multi-Slice CT-technology allows extending this morphological analysis by adding a more functional visualization of the actual parenchymal perfusion disturbance. We have developed a new image processing technique which allows selective color encoded display of parenchymal enhancement of the lung, which will be reduced in the presence of PE. Based on thin slice reconstructions an automatic 3D segmentation of the lung is performed followed by threshold based extraction of the major airways and vascular structures. This allows applying an adaptive 3D low-pass filter to the parenchymal volume only. The filtered volume data are then color encoded and overlaid onto the original CT-images. This combination of low-resolution perfusion-weighted color maps and high-resolution gray scale structural data from the same data set greatly enhances visualization of spatial relationships. The resulting images can be displayed in axial, sagittal and coronal orientation. Initial experience indicates that this new technique provides relevant additional information for the clinical management of patients with proven PE. A larger controlled patient study is under way.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Matthias U. Niethammer, Uwe Joseph Schoepf, Hoachim E. Wildberger, Ernst Klotz, Heinz Fichte, and Stefan Schaller "New approach to diagnosis of pulmonary embolism using multislice CT", Proc. SPIE 4321, Medical Imaging 2001: Physiology and Function from Multidimensional Images, (21 May 2001); https://doi.org/10.1117/12.428142
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Cited by 3 scholarly publications.
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KEYWORDS
Lung

Computed tomography

Image segmentation

Diagnostics

Image processing

Angiography

Visualization

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