Scatter correction for positron emission mammography

Qi, Jinyi; Huesman, R.H.

doi:10.1088/0031-9155/47/15/315

Cited by 27 publications

(16 citation statements)

References 20 publications

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“…Simulation studies for a bPET system with improved chest wall coverage, lower average energy resolution, and higher photon sensitivity than DbPET/CT, however, revealed that the contribution to the total SF from OFOV activity is expected to be negligible. 46 Several artifacts were evident in images of a uniform cylinder even after application of all corrections. Most visible was a low magnitude concentric ring pattern (Fig.…”

Section: Discussionmentioning

confidence: 98%

Quantification with a dedicated breast PET/CT scanner

2012

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Purpose: Dedicated breast PET/CT is expected to have utility in local staging, surgical planning, monitoring of therapy response, and detection of residual disease for breast cancer. Quantitative metrics will be integral to several such applications. The authors present a validation of fully 3D data correction schemes for a custom built dedicated breast PET/CT (DbPET/CT) scanner via 18 F-FDG phantom scans. Methods: A component-based normalization was implemented, live-time was estimated with a multicomponent model, and a variance reduced randoms estimate was computed from delayed coincidences. Attenuation factors were calculated by using a CT based segmentation scheme while scatter was computed using a Monte Carlo (MC) simulation method. As no performance standard currently exists for breast PET systems, custom performance tests were created based on prior patient imaging results. Count-rate linearity for live-time and randoms corrections was measured with a decay experiment for a solid polyethylene cylinder phantom with an offset line source. A MC simulation was used to validate attenuation correction, a multicompartment phantom with asymmetric activity distribution provided an assessment of scatter correction, and image uniformity after geometric and detector normalization was measured from a high count scan of a uniform cylinder phantom. Raw data were reconstructed with filtered back projection (FBP) after Fourier rebinning. To quantify performance absolute activity concentrations, contrast recovery coefficients and image uniformity were calculated through region of interest analysis. Results: The most significant source of error was attributed to mispositioning of events due to pileup, presenting in count-related axial and transaxial nonuniformities that were not corrected for with the normalization method used here. Within the range of singles counts observed during clinical trials residual error after applying all corrections was comparable to that of a commercial whole body PET/CT system. Conclusions: The results suggest that DbPET/CT is capable of producing quantitative images under the operating conditions expected during patient imaging. V C 2012 American Association of Physicists in Medicine. [http://dx

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Section: Discussionmentioning

confidence: 98%

Quantification with a dedicated breast PET/CT scanner

2012

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“…Because scatters and random events increase the number of counts of prompt data, they can improve the accuracy of the variance estimated by the data plug-in method (Qi and Leahy 2000). We note that imperfect scatter and random corrections can introduce additional variance in reconstructed images (Qi and Huesman 2002), but such corrections are unnecessary for lesion detection because these background events result in a common bias for both H 0 and H 1 hypotheses and doe not affect the lesion detectability for a well-trained observer. This is similar to the case where non-attenuation corrected PET images have been widely used before PET/CT was introduced.…”

Section: Discussionmentioning

confidence: 99%

Regularization design in penalized maximum-likelihood image reconstruction for lesion detection in 3D PET

et al. 2013

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Detecting cancerous lesions is a major clinical application in emission tomography. In previous work, we have studied penalized maximum-likelihood (PML) image reconstruction for the detection task and proposed a method to design a shift-invariant quadratic penalty function to maximize detectability of a lesion at a known location in a two dimensional (2D) image. Here we extend the regularization design to maximize detectability of lesions at unknown locations in fully 3D PET. We used a multiview channelized Hotelling observer (mvCHO) to assess the lesion detectability in 3D images to mimic the condition where a human observer examines three orthogonal views of a 3D image for lesion detection. We derived simplified theoretical expressions that allow fast prediction of the detectability of a 3D lesion. The theoretical results were used to design the regularization in PML reconstruction to improve lesion detectability. We conducted computer-based Monte Carlo simulations to compare the optimized penalty with the conventional penalty for detecting lesions of various sizes. Only true coincidence events were simulated. Lesion detectability was also assessed by two human observers, whose performances agree well with that of the mvCHO. Both the numerical observer and human observer results showed a statistically significant improvement in lesion detection by using the proposed penalty function compared to using the conventional penalty function.

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“…It has been shown that the derivative of the reconstructed image x with respect to the background term r is 41,42 …”

Section: Iic Artifact Correctionmentioning

confidence: 99%

A residual correction method for high‐resolution PET reconstruction with application to on‐the‐fly Monte Carlo based model of positron range

2010

Medical Physics

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Purpose: The quality of tomographic images is directly affected by the system model being used in image reconstruction. An accurate system matrix is desirable for high-resolution image reconstruction, but it often leads to high computation cost. In this work the authors present a maximum a posteriori reconstruction algorithm with residual correction to alleviate the tradeoff between the model accuracy and the computation efficiency in image reconstruction. Methods: Unlike conventional iterative methods that assume that the system matrix is accurate, the proposed method reconstructs an image with a simplified system matrix and then removes the reconstruction artifacts through residual correction. Since the time-consuming forward and back projection operations using the accurate system matrix are not required in every iteration, image reconstruction time can be greatly reduced. Results:The authors apply the new algorithm to high-resolution positron emission tomography reconstruction with an on-the-fly Monte Carlo ͑MC͒ based positron range model. Computer simulations show that the new method is an order of magnitude faster than the traditional MC-based method, whereas the visual quality and quantitative accuracy of the reconstructed images are much better than that obtained by using the simplified system matrix alone. Conclusions:The residual correction method can reconstruct high-resolution images and is computationally efficient.

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Scatter correction for positron emission mammography

Cited by 27 publications

References 20 publications

Quantification with a dedicated breast PET/CT scanner

Quantification with a dedicated breast PET/CT scanner

Regularization design in penalized maximum-likelihood image reconstruction for lesion detection in 3D PET

A residual correction method for high‐resolution PET reconstruction with application to on‐the‐fly Monte Carlo based model of positron range

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