Dr. Alexander Hans Vija Profile

Dr. Alexander Hans Vija

at Siemens Healthineers

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Proceedings Article | 29 April 2005 Paper

Statistically based spatially adaptive noise reduction of planar nuclear studies

A. Hans Vija, Timothy Gosnell, Amos Yahil, Eric Hawman, John Engdahl

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.595679

KEYWORDS: Image processing, Optical spheres, Denoising, Image filtering, Image quality, Data acquisition, Nuclear medicine, Smoothing, Sensors, Digital filtering

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The data-driven Pixon noise-reduction method is applied to nuclear studies. By using the local information content, it preserves all statistically justifiable image features without generating artifacts. Statistical measures provide the user a feedback to judge if the processing parameters are optimal. The present work focuses on planar nuclear images with known Poisson noise characteristics. Its ultimate goals are to: (a) increase sensitivity for detection of lesions of small size and/or of small activity-to-background ratio, (b) reduce data acquisition time, and (c) reduce patient dose. Data are acquired using Data Spectrum’s cylinder phantom in two configurations: (a) with hot and cold rod inserts at varying total counts and (b) with hot sphere inserts at varying activity-to-background ratios. We show that the method adapts automatically to both hot and cold lesions, concentration ratios, and different noise levels and structure dimensions. In clinical applications, slight adjustment of the parameters may be needed to adapt to the specific clinical protocols and physician preference. Visually, the processed images are comparable to raw images with ~16 times as many counts, and quantitatively the reduced noise equals that obtained with ~50 times as many counts. We also show that the Pixon method allows for identification of spheres at low concentration ratios, where raw planar imaging fails and matched filtering underperforms. Conclusion: The Pixon method significantly improves the image quality of data at either reduced count levels, or low target-to-background ratios. An analysis of clinical studies is now warranted to assess the clinical impact of the method.

Proceedings Article | 20 April 2005 Paper

Line array transmission sources for SPECT attenuation correction—design and reconstruction

E. Hawman, T. Rempel, A. Vija, J. Engdahl

Proceedings Volume 5745, (2005) https://doi.org/10.1117/12.596081

KEYWORDS: Signal attenuation, Reconstruction algorithms, Single photon emission computed tomography, Sensors, Image quality, Detection and tracking algorithms, Cameras, Transmittance, Algorithm development, Spatial resolution

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Correction for non-uniform attenuation in SPECT generally requires measurements of radiation transmittance through the patient and reconstruction of the data to form an attenuation image, or mu-map. For nuclear cardiac studies it useful if the emission and transmission data for each projection view can be acquired simultaneously using non-overlapping energy windows. This simplifies the registration of the emission and transmission data. Large area transmission sources are desirable to avoid data truncation; however, 2D-planar liquid sources are cumbersome and extended solid area sources of Gd-153 or Am-247 are impractical. Co-57 sheet sources present spectral overlap problems for imaging of Tc-99m tracers. With Gd-153 line arrays, one can achieve the benefits of 2D-planar sources, low truncation and simultaneous emission/transmission measurements, using lightweight static mechanical attachments to the SPECT camera system. A new method is proposed to determine optimal positions for the lines of the transmission array based on maximizing the entropy of the transmitted flux through the patient. Transmission reconstruction using parallel beam filtered back-projection yields attenuation maps with poor spatial resolution and significant aliasing effects. The degradations of image quality become worse as the angular separations of the lines as seen by the detector increase. To improve the reconstruction of line array transmission data a maximum likelihood modified gradient algorithm was derived. The algorithm takes into account emission-to-transmission down scatter as well as the overlapping of radiation patterns of the individual lines. Ordered subset versions of algorithms are explored. Image quality is assessed with simulations based on an attenuation map derived from CT.

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