Scatter correction for 3-D PET by convolution of plane-integral projections

2005 ◽  
Author(s):  
Chunwu Wu ◽  
C.E. Ordonez ◽  
Chin-Tu Chen
Keyword(s):  
Scatter Correction

Quantitative accuracy of serotonergic neurotrans-mission imaging with high-resolution 123I SPECT

2004 ◽  
Vol 43 (06) ◽  
pp. 185-189 ◽  
Author(s):  
J. T. Kuikka
Keyword(s):  
High Resolution ◽  
Scatter Correction ◽  
Region Of Interest ◽  
Binding Potential ◽  
Partial Volume ◽  
Therapeutic Drugs ◽  
Quantitative Accuracy ◽  
Critical Error ◽  
Statistical Noise

Summary Aim: Serotonin transporter (SERT) imaging can be used to study the role of regional abnormalities of neurotransmitter release in various mental disorders and to study the mechanism of action of therapeutic drugs or drugs’ abuse. We examine the quantitative accuracy and reproducibility that can be achieved with high-resolution SPECT of serotonergic neurotransmission. Method: Binding potential (BP) of 123I labeled tracer specific for midbrain SERT was assessed in 20 healthy persons. The effects of scatter, attenuation, partial volume, mis-registration and statistical noise were estimated using phantom and human studies. Results: Without any correction, BP was underestimated by 73%. The partial volume error was the major component in this underestimation whereas the most critical error for the reproducibility was misplacement of region of interest (ROI). Conclusion: The proper ROI registration, the use of the multiple head gamma camera with transmission based scatter correction introduce more relevant results. However, due to the small dimensions of the midbrain SERT structures and poor spatial resolution of SPECT, the improvement without the partial volume correction is not great enough to restore the estimate of BP to that of the true one.

scholarly journals Accurate Transmission-Less Attenuation Correction Method for Amyloid-β Brain PET Using Deep Neural Network

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1836
Author(s):  
Bo-Hye Choi ◽  
Donghwi Hwang ◽  
Seung-Kwan Kang ◽  
Kyeong-Yun Kim ◽  
Hongyoon Choi ◽  
...  
Keyword(s):  
Neural Network ◽  
Attenuation Correction ◽  
Complex Structure ◽  
Scatter Correction ◽  
Amyloid Β ◽  
Correction Method ◽  
Percentage Error ◽  
Similarity Coefficients ◽  
Brain Pet ◽  
Positron Emission

The lack of physically measured attenuation maps (μ-maps) for attenuation and scatter correction is an important technical challenge in brain-dedicated stand-alone positron emission tomography (PET) scanners. The accuracy of the calculated attenuation correction is limited by the nonuniformity of tissue composition due to pathologic conditions and the complex structure of facial bones. The aim of this study is to develop an accurate transmission-less attenuation correction method for amyloid-β (Aβ) brain PET studies. We investigated the validity of a deep convolutional neural network trained to produce a CT-derived μ-map (μ-CT) from simultaneously reconstructed activity and attenuation maps using the MLAA (maximum likelihood reconstruction of activity and attenuation) algorithm for Aβ brain PET. The performance of three different structures of U-net models (2D, 2.5D, and 3D) were compared. The U-net models generated less noisy and more uniform μ-maps than MLAA μ-maps. Among the three different U-net models, the patch-based 3D U-net model reduced noise and cross-talk artifacts more effectively. The Dice similarity coefficients between the μ-map generated using 3D U-net and μ-CT in bone and air segments were 0.83 and 0.67. All three U-net models showed better voxel-wise correlation of the μ-maps compared to MLAA. The patch-based 3D U-net model was the best. While the uptake value of MLAA yielded a high percentage error of 20% or more, the uptake value of 3D U-nets yielded the lowest percentage error within 5%. The proposed deep learning approach that requires no transmission data, anatomic image, or atlas/template for PET attenuation correction remarkably enhanced the quantitative accuracy of the simultaneously estimated MLAA μ-maps from Aβ brain PET.

scholarly journals Optimization of SPECT/CT imaging protocols for quantitative and qualitative 99mTc SPECT

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Dennis Kupitz ◽  
Heiko Wissel ◽  
Jan Wuestemann ◽  
Stephanie Bluemel ◽  
Maciej Pech ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Quantitative Imaging ◽  
Scatter Correction ◽  
Reconstruction Algorithm ◽  
Weighting Factor ◽  
Quantitative Spect ◽  
Pet Ct ◽  
Spect Acquisition ◽  
The Mean ◽  
A Minor

Abstract Background The introduction of hybrid SPECT/CT devices enables quantitative imaging in SPECT, providing a methodological setup for quantitation using SPECT tracers comparable to PET/CT. We evaluated a specific quantitative reconstruction algorithm for SPECT data using a 99mTc-filled NEMA phantom. Quantitative and qualitative image parameters were evaluated for different parametrizations of the acquisition and reconstruction protocol to identify an optimized quantitative protocol. Results The reconstructed activity concentration (ACrec) and the signal-to-noise ratio (SNR) of all examined protocols (n = 16) were significantly affected by the parametrization of the weighting factor k used in scatter correction, the total number of iterations and the sphere volume (all, p < 0.0001). The two examined SPECT acquisition protocols (with 60 or 120 projections) had a minor impact on the ACrec and no significant impact on the SNR. In comparison to the known AC, the use of default scatter correction (k = 0.47) or object-specific scatter correction (k = 0.18) resulted in an underestimation of ACrec in the largest sphere volume (26.5 ml) by − 13.9 kBq/ml (− 16.3%) and − 7.1 kBq/ml (− 8.4%), respectively. An increase in total iterations leads to an increase in estimated AC and a decrease in SNR. The mean difference between ACrec and known AC decreased with an increasing number of total iterations (e.g., for 20 iterations (2 iterations/10 subsets) = − 14.6 kBq/ml (− 17.1%), 240 iterations (24i/10s) = − 8.0 kBq/ml (− 9.4%), p < 0.0001). In parallel, the mean SNR decreased significantly from 2i/10s to 24i/10s by 76% (p < 0.0001). Conclusion Quantitative SPECT imaging is feasible with the used reconstruction algorithm and hybrid SPECT/CT, and its consistent implementation in diagnostics may provide perspectives for quantification in routine clinical practice (e.g., assessment of bone metabolism). When combining quantitative analysis and diagnostic imaging, we recommend using two different reconstruction protocols with task-specific optimized setups (quantitative vs. qualitative reconstruction). Furthermore, individual scatter correction significantly improves both quantitative and qualitative results.

scholarly journals Monte Carlo-based scatter correction for the SMARTZOOM collimator

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Martijn M. A. Dietze ◽  
Britt Kunnen ◽  
Martina Stella ◽  
Hugo W. A. M. de Jong
Keyword(s):  
Monte Carlo ◽  
Scatter Correction

Algorithmic scatter correction in dual-energy digital mammography for calcification imaging

2012 ◽  
Author(s):  
Xi Chen ◽  
Robert M. Nishikawa ◽  
Suk-Tak Chan ◽  
Beverly A. Lau ◽  
Lei Zhang ◽  
...  
Keyword(s):  
Digital Mammography ◽  
Scatter Correction ◽  
Dual Energy

Impact on dose and image quality of a software-based scatter correction in mammography

2017 ◽  
Vol 59 (6) ◽  
pp. 649-656 ◽  
Author(s):  
Teresa Monserrat ◽  
Elena Prieto ◽  
Benigno Barbés ◽  
Luis Pina ◽  
Arlette Elizalde ◽  
...  
Keyword(s):  
Image Quality ◽  
Scatter Correction ◽  
Inverse Image ◽  
Clinical Image ◽  
Air Kerma ◽  
Average Glandular Dose ◽  
Standard Mode ◽  
Entrance Surface Air Kerma ◽  
Clinical Cases

Background In 2014, Siemens developed a new software-based scatter correction (Progressive Reconstruction Intelligently Minimizing Exposure [PRIME]), enabling grid-less digital mammography. Purpose To compare doses and image quality between PRIME (grid-less) and standard (with anti-scatter grid) modes. Material and Methods Contrast-to-noise ratio (CNR) was measured for various polymethylmethacrylate (PMMA) thicknesses and dose values provided by the mammograph were recorded. CDMAM phantom images were acquired for various PMMA thicknesses and inverse Image Quality Figure (IQFinv) was calculated. Values of incident entrance surface air kerma (ESAK) and average glandular dose (AGD) were obtained from the DICOM header for a total of 1088 pairs of clinical cases. Two experienced radiologists compared subjectively the image quality of a total of 149 pairs of clinical cases. Results CNR values were higher and doses were lower in PRIME mode for all thicknesses. IQFinv values in PRIME mode were lower for all thicknesses except for 40 mm of PMMA equivalent, in which IQFinv was slightly greater in PRIME mode. A mean reduction of 10% in ESAK and 12% in AGD in PRIME mode with respect to standard mode was obtained. The clinical image quality in PRIME and standard acquisitions resulted to be similar in most of the cases (84% for the first radiologist and 67% for the second one). Conclusion The use of PRIME software reduces, in average, the dose of radiation to the breast without affecting image quality. This reduction is greater for thinner and denser breasts.

scholarly journals Mie scatter corrections in single cell infrared microspectroscopy

2016 ◽  
Vol 187 ◽  
pp. 235-257 ◽  
Author(s):  
Tatiana Konevskikh ◽  
Rozalia Lukacs ◽  
Reinhold Blümel ◽  
Arkadi Ponossov ◽  
Achim Kohler
Keyword(s):  
Iterative Algorithm ◽  
Single Cells ◽  
Scatter Correction ◽  
Numerical Aperture ◽  
Mie Scattering ◽  
Infrared Light ◽  
Approximation Formula ◽  
Meta Model ◽  
Independent Parameters ◽  
Absorbance Spectra

Strong Mie scattering signatures hamper the chemical interpretation and multivariate analysis of the infrared microscopy spectra of single cells and tissues. During recent years, several numerical Mie scatter correction algorithms for the infrared spectroscopy of single cells have been published. In the paper at hand, we critically reviewed existing algorithms for the correction of Mie scattering and suggest improvements. We developed an iterative algorithm based on Extended Multiplicative Scatter Correction (EMSC), for the retrieval of pure absorbance spectra from highly distorted infrared spectra of single cells. The new algorithm uses the van de Hulst approximation formula for the extinction efficiency employing a complex refractive index. The iterative algorithm involves the establishment of an EMSC meta-model. While existing iterative algorithms for the correction of resonant Mie scattering employ three independent parameters for establishing a meta-model, we could decrease the number of parameters from three to two independent parameters, which reduced the calculation time for the Mie scattering curves for the iterative EMSC meta-model by a factor of 10. Moreover, by employing the Hilbert transform for evaluating the Kramers–Kronig relations based on a FFT algorithm in Matlab, we further improved the speed of the algorithm by a factor of 100. For testing the algorithm we simulate distorted apparent absorbance spectra by utilizing the exact theory for the scattering of infrared light at absorbing spheres, taking into account the high numerical aperture of infrared microscopes employed for the analysis of single cells and tissues. In addition, the algorithm was applied to measured absorbance spectra of single lung cancer cells.

Scatter correction of vessel dropout behind highly attenuating structures in 4D-DSA

2015 ◽  
Author(s):  
James Hermus ◽  
Charles Mistretta ◽  
Timothy P. Szczykutowicz
Keyword(s):  
Scatter Correction
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