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1.
NMR Biomed ; 34(1): e4420, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33021342

RESUMO

INTRODUCTION: Magnetic resonance elastography (MRE)-derived aortic stiffness is a potential biomarker for multiple cardiovascular diseases. Currently, gradient-recalled echo (GRE) MRE is a widely accepted technique to estimate aortic stiffness. However, multi-slice GRE MRE requires multiple breath-holds (BHs), which can be challenging for patients who cannot consistently hold their breath. The aim of this study was to investigate the feasibility of a multi-slice spin-echo echo-planar imaging (SE-EPI) MRE sequence for quantifying in vivo aortic stiffness using a free-breathing (FB) protocol and a single-BH protocol. METHOD: On Scanner 1, 25 healthy subjects participated in the validation of FB SE-EPI against FB GRE. On Scanner 2, another 15 healthy subjects were recruited to compare FB SE-EPI with single-BH SE-EPI. Among all volunteers, five participants were studied on both scanners to investigate the inter-scanner reproducibility of FB SE-EPI aortic MRE. Bland-Altman analysis, Lin's concordance correlation coefficient (LCCC) and coefficient of variation (COV) were evaluated. The phase-difference signal-to-noise ratios (PD SNR) were compared. RESULTS: Aortic MRE using FB SE-EPI and FB GRE yielded similar stiffnesses (paired t-test, P = 0.19), with LCCC = 0.97. The FB SE-EPI measurements were reproducible (intra-scanner LCCC = 0.96) and highly repeatable (LCCC = 0.99). The FB SE-EPI MRE was also reproducible across different scanners (inter-scanner LCCC = 0.96). Single-BH SE-EPI scans yielded similar stiffness to FB SE-EPI scans (LCCC = 0.99) and demonstrated a low COV of 2.67% across five repeated measurements. CONCLUSION: Multi-slice SE-EPI aortic MRE using an FB protocol or a single-BH protocol is reproducible and repeatable with advantage over multi-slice FB GRE in reducing acquisition time. Additionally, FB SE-EPI MRE provides a potential alternative to BH scans for patients who have challenges in holding their breath.


Assuntos
Aorta Abdominal/diagnóstico por imagem , Técnicas de Imagem de Sincronização Cardíaca/métodos , Técnicas de Imagem por Elasticidade/métodos , Imagem por Ressonância Magnética/métodos , Rigidez Vascular , Aorta Abdominal/fisiologia , Técnicas de Imagem de Sincronização Cardíaca/instrumentação , Imagem Ecoplanar/instrumentação , Imagem Ecoplanar/métodos , Técnicas de Imagem por Elasticidade/instrumentação , Estudos de Viabilidade , Humanos , Imagem por Ressonância Magnética/instrumentação , Valores de Referência , Reprodutibilidade dos Testes , Respiração , Razão Sinal-Ruído
2.
Br J Radiol ; 94(1117): 20200677, 2021 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-33095654

RESUMO

OBJECTIVES: Modern reconstruction and post-processing software aims at reducing image noise in CT images, potentially allowing for a reduction of the employed radiation exposure. This study aimed at assessing the influence of a novel deep-learning based software on the subjective and objective image quality compared to two traditional methods [filtered back-projection (FBP), iterative reconstruction (IR)]. METHODS: In this institutional review board-approved retrospective study, abdominal low-dose CT images of 27 patients (mean age 38 ± 12 years, volumetric CT dose index 2.9 ± 1.8 mGy) were reconstructed with IR, FBP and, furthermore, post-processed using a novel software. For the three reconstructions, qualitative and quantitative image quality was evaluated by means of CT numbers, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in six different ROIs. Additionally, the reconstructions were compared using SNR, peak SNR, root mean square error and mean absolute error to assess structural differences. RESULTS: On average, CT numbers varied within 1 Hounsfield unit (HU) for the three assessed methods in the assessed ROIs. In soft tissue, image noise was up to 42% lower compared to FBP and up to 27% lower to IR when applying the novel software. Consequently, SNR and CNR were highest with the novel software. For both IR and the novel software, subjective image quality was equal but higher than the image quality of FBP-images. CONCLUSION: The assessed software reduces image noise while maintaining image information, even in comparison to IR, allowing for a potential dose reduction of approximately 20% in abdominal CT imaging. ADVANCES IN KNOWLEDGE: The assessed software reduces image noise by up to 27% compared to IR and 48% compared to FBP while maintaining the image information.The reduced image noise allows for a potential dose reduction of approximately 20% in abdominal imaging.


Assuntos
Interpretação de Imagem Assistida por Computador/métodos , Doses de Radiação , Radiografia Abdominal/métodos , Tomografia Computadorizada por Raios X/métodos , Abdome/diagnóstico por imagem , Adulto , Aprendizado Profundo , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Razão Sinal-Ruído , Adulto Jovem
3.
PET Clin ; 16(1): 89-97, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33160926

RESUMO

Total-body PET enables high-sensitivity imaging with dramatically improved signal-to-noise ratio. These enhanced performance characteristics allow for decreased PET scanning times acquiring data "total-body wide" and can be leveraged to decrease the amount of radiotracer required, thereby permitting more frequent imaging or longer imaging periods during radiotracer decay. Novel approaches to PET imaging of infectious diseases are emerging, including those that directly visualize pathogens in vivo and characterize concomitant immune responses and inflammation. Efforts to develop these imaging approaches are hampered by challenges of traditional imaging platforms, which may be overcome by novel total-body PET strategies.


Assuntos
Doenças Transmissíveis/diagnóstico por imagem , Tomografia por Emissão de Pósitrons/métodos , Imagem Corporal Total/métodos , Humanos , Razão Sinal-Ruído , Tempo
4.
Phys Med Biol ; 65(22): 225004, 2020 12 07.
Artigo em Inglês | MEDLINE | ID: mdl-33284786

RESUMO

Electronic portal imaging devices (EPIDs) lend themselves to beams-eye view clinical applications, such as tumor tracking, but are limited by low contrast and detective quantum efficiency (DQE). We characterize a novel EPID prototype consisting of multiple layers and investigate its suitability for use under clinical conditions. A prototype multi-layer imager (MLI) was constructed utilizing four conventional EPID layers, each consisting of a copper plate, a Gd2O2S:Tb phosphor scintillator, and an amorphous silicon flat panel array detector. We measured the detector's response to a 6 MV photon beam with regards to modulation transfer function, noise power spectrum, DQE, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and the linearity of the detector's response to dose. Additionally, we compared MLI performance to the single top layer of the MLI and the standard Varian AS-1200 detector. Pre-clinical imaging was done on an anthropomorphic phantom, and the detector's CNR, SNR and spatial resolution were assessed in a clinical environment. Images obtained from spine and liver patient treatment deliveries were analyzed to verify CNR and SNR improvements. The MLI has a DQE(0) of 9.7%, about 5.7 times the reference AS-1200 detector. Improved noise performance largely drives the increase. CNR and SNR of clinical images improved three-fold compared to reference. A novel MLI was characterized and prepared for clinical translation. The MLI substantially improved DQE and CNR performance while maintaining the same resolution. Pre-clinical tests on an anthropomorphic phantom demonstrated improved performance as predicted theoretically. Preliminary patient data were analyzed, confirming improved CNR and SNR. Clinical applications are anticipated to include more accurate soft tissue tracking.


Assuntos
Diagnóstico por Imagem/instrumentação , Equipamentos e Provisões Elétricas , Humanos , Imagens de Fantasmas , Razão Sinal-Ruído , Pesquisa Médica Translacional
5.
BMC Bioinformatics ; 21(Suppl 21): 534, 2020 Dec 28.
Artigo em Inglês | MEDLINE | ID: mdl-33371884

RESUMO

BACKGROUND: Cryo-EM data generated by electron tomography (ET) contains images for individual protein particles in different orientations and tilted angles. Individual cryo-EM particles can be aligned to reconstruct a 3D density map of a protein structure. However, low contrast and high noise in particle images make it challenging to build 3D density maps at intermediate to high resolution (1-3 Å). To overcome this problem, we propose a fully automated cryo-EM 3D density map reconstruction approach based on deep learning particle picking. RESULTS: A perfect 2D particle mask is fully automatically generated for every single particle. Then, it uses a computer vision image alignment algorithm (image registration) to fully automatically align the particle masks. It calculates the difference of the particle image orientation angles to align the original particle image. Finally, it reconstructs a localized 3D density map between every two single-particle images that have the largest number of corresponding features. The localized 3D density maps are then averaged to reconstruct a final 3D density map. The constructed 3D density map results illustrate the potential to determine the structures of the molecules using a few samples of good particles. Also, using the localized particle samples (with no background) to generate the localized 3D density maps can improve the process of the resolution evaluation in experimental maps of cryo-EM. Tested on two widely used datasets, Auto3DCryoMap is able to reconstruct good 3D density maps using only a few thousand protein particle images, which is much smaller than hundreds of thousands of particles required by the existing methods. CONCLUSIONS: We design a fully automated approach for cryo-EM 3D density maps reconstruction (Auto3DCryoMap). Instead of increasing the signal-to-noise ratio by using 2D class averaging, our approach uses 2D particle masks to produce locally aligned particle images. Auto3DCryoMap is able to accurately align structural particle shapes. Also, it is able to construct a decent 3D density map from only a few thousand aligned particle images while the existing tools require hundreds of thousands of particle images. Finally, by using the pre-processed particle images, Auto3DCryoMap reconstructs a better 3D density map than using the original particle images.


Assuntos
Microscopia Crioeletrônica , Imageamento Tridimensional/métodos , Algoritmos , Automação , Proteínas/química , Razão Sinal-Ruído
6.
Phys Med Biol ; 65(21): 215025, 2020 11 27.
Artigo em Inglês | MEDLINE | ID: mdl-33245059

RESUMO

Correcting or reducing the effects of voxel intensity non-uniformity (INU) within a given tissue type is a crucial issue for quantitative magnetic resonance (MR) image analysis in daily clinical practice. Although having no severe impact on visual diagnosis, the INU can highly degrade the performance of automatic quantitative analysis such as segmentation, registration, feature extraction and radiomics. In this study, we present an advanced deep learning based INU correction algorithm called residual cycle generative adversarial network (res-cycle GAN), which integrates the residual block concept into a cycle-consistent GAN (cycle-GAN). In cycle-GAN, an inverse transformation was implemented between the INU uncorrected and corrected magnetic resonance imaging (MRI) images to constrain the model through forcing the calculation of both an INU corrected MRI and a synthetic corrected MRI. A fully convolution neural network integrating residual blocks was applied in the generator of cycle-GAN to enhance end-to-end raw MRI to INU corrected MRI transformation. A cohort of 55 abdominal patients with T1-weighted MR INU images and their corrections with a clinically established and commonly used method, namely, N4ITK were used as a pair to evaluate the proposed res-cycle GAN based INU correction algorithm. Quantitatively comparisons of normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC) indices, and spatial non-uniformity (SNU) were made among the proposed method and other approaches. Our res-cycle GAN based method achieved an NMAE of 0.011 ± 0.002, a PSNR of 28.0 ± 1.9 dB, an NCC of 0.970 ± 0.017, and a SNU of 0.298 ± 0.085. Our proposed method has significant improvements (p < 0.05) in NMAE, PSNR, NCC and SNU over other algorithms including conventional GAN and U-net. Once the model is well trained, our approach can automatically generate the corrected MR images in a few minutes, eliminating the need for manual setting of parameters.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Imagem por Ressonância Magnética , Redes Neurais de Computação , Humanos , Razão Sinal-Ruído
7.
Phys Med Biol ; 65(22): 225020, 2020 11 17.
Artigo em Inglês | MEDLINE | ID: mdl-33200748

RESUMO

Dynamic susceptibility contrast (DSC) imaging is a widely used technique for assessment of cerebral blood volume (CBV). With combined gradient-echo and spin-echo DSC techniques, measures of the underlying vessel size and vessel architecture can be obtained from the vessel size index (VSI) and vortex area, respectively. However, how noise, and specifically the contrast-to-noise ratio (CNR), affect the estimations of these parameters has largely been overlooked. In order to address this issue, we have performed simulations to generate DSC signals with varying levels of CNR, defined by the peak of relaxation rate curve divided by the standard deviation of the baseline. Moreover, DSC data from 59 brain cancer patients were acquired at two different 3 T-scanners (N = 29 and N = 30, respectively), where CNR and relative parameter maps were obtained. Our simulations showed that the measured parameters were affected by CNR in different ways, where low CNR led to overestimations of CBV and underestimations of VSI and vortex area. In addition, a higher noise-sensitivity was found in vortex area than in CBV and VSI. Results from clinical data were consistent with simulations, and indicated that CNR < 4 gives highly unreliable measurements. Moreover, we have shown that the distribution of values in the tumour regions could change considerably when voxels with CNR below a given cut off are excluded when generating the relative parameter maps. The widespread use of CBV and attractive potential of VSI and vortex area, makes the noise-sensitivity of these parameters found in our study relevant for further use and development of the DSC imaging technique. Our results suggest that the CNR has considerable impact on the measured parameters, with the potential to affect the clinical interpretation of DSC-MRI, and should therefore be taken into account in the clinical decision-making process.


Assuntos
Vasos Sanguíneos/diagnóstico por imagem , Imagem por Ressonância Magnética/métodos , Razão Sinal-Ruído , Adulto , Neoplasias Encefálicas/irrigação sanguínea , Neoplasias Encefálicas/diagnóstico por imagem , Feminino , Humanos , Masculino , Pessoa de Meia-Idade
8.
Phys Med Biol ; 65(22): 225028, 2020 11 24.
Artigo em Inglês | MEDLINE | ID: mdl-33231200

RESUMO

This work compared the impact of x-ray tube performance and automatic dose rate control (ADRC) parameter selection on system imaging efficiency of two Siemens angiography systems: a Siemens Megalix x-ray tube installed on an Artis Zee system (denoted 'MEGALIX') and a newer generation Gigalix x-ray tube installed on an Artis Q (denoted 'GIGALIX'). A method was used that accounted for two potential sources of bias in this comparison: differences in radiation output between the x-ray tubes and differences between the x-ray detectors on the two systems. First, ADRC x-ray factors (tube voltage, tube current, pulse length, focus size, spectral prefilter) and radiation output were recorded as a function of poly(methyl) methacrylate (PMMA) thickness on the MEGALIX unit. These factors were then applied manually on the GIGALIX system and incident air kerma rate (IAKR) and signal difference to noise ratio (SDNR) were measured. Second, the ADRC on the GIGALIX system was used to give the x-ray factors and both IAKR and SDNR relevant to the GIGALIX based system directly. This method enabled the SDNR to be measured from images acquired on the same x-ray detector. SDNR and IAKR were measured on both systems using a PMMA phantom covering thicknesses from 6 cm to 40 cm. A small 0.3 mm iron insert was used to measure SDNR, which was then multiplied by modulation transfer function based weighting factors for focal spot blurring and motion blurring. These factors were evaluated for an object motion of 25 mm s-1 and at a spatial frequency of 1.4 mm-1 in the object plane, relevant to interventional cardiology, giving a spatial frequency dependent SDNR(u). In the second phase of the study, a technical figure of merit (FOM) was used to express imaging performance of both systems, calculated as SDNR2(u)/IAKR. Averaged over all phantom thicknesses, the FOM of the GIGALIX-based system was 42% and 73% higher compared to that of the MEGALIX based system, for fluoroscopy and acquisition mode respectively. The results indicate that increased x-ray tube power and smaller foci can improve overall system efficiency and reduce doses.


Assuntos
Angiografia/instrumentação , Ar , Humanos , Imagens de Fantasmas , Polimetil Metacrilato , Doses de Radiação , Razão Sinal-Ruído , Raios X
9.
Phys Med Biol ; 65(22): 225035, 2020 11 24.
Artigo em Inglês | MEDLINE | ID: mdl-33231201

RESUMO

In this work we model the noise properties of a computed radiography (CR) mammography system by adding an extra degree of freedom to a well-established noise model, and derive a variance-stabilizing transform (VST) to convert the signal-dependent noise into approximately signal-independent. The proposed model relies on a quadratic variance function, which considers fixed-pattern (structural), quantum and electronic noise. It also accounts for the spatial-dependency of the noise by assuming a space-variant quantum coefficient. The proposed noise model was compared against two alternative models commonly found in the literature. The first alternative model ignores the spatial-variability of the quantum noise, and the second model assumes negligible structural noise. We also derive a VST to convert noisy observations contaminated by the proposed noise model into observations with approximately Gaussian noise and constant variance equals to one. Finally, we estimated a look-up table that can be used as an inverse transform in denoising applications. A phantom study was conducted to validate the noise model, VST and inverse VST. The results show that the space-variant signal-dependent quadratic noise model is appropriate to describe noise in this CR mammography system (errors< 2.0% in terms of signal-to-noise ratio). The two alternative noise models were outperformed by the proposed model (errors as high as 14.7% and 9.4%). The designed VST was able to stabilize the noise so that it has variance approximately equal to one (errors< 4.1%), while the two alternative models achieved errors as high as 26.9% and 18.0%, respectively. Finally, the proposed inverse transform was capable of returning the signal to the original signal range with virtually no bias.


Assuntos
Mamografia , Modelos Teóricos , Razão Sinal-Ruído , Algoritmos , Humanos , Distribuição Normal , Imagens de Fantasmas
10.
Phys Med Biol ; 65(22): 225030, 2020 11 24.
Artigo em Inglês | MEDLINE | ID: mdl-33231202

RESUMO

X-ray CT polymer gel dosimetry (PGD) remains a promising tool for three dimensional verification of high-dose treatment deliveries such as non-coplanar stereotactic irradiations. Recent demonstrations have shown a proof-of-principle application of linac-integrated cone beam CT-imaged (LI-CBCT) PGDs for 3D dose verification. LI-CBCT offers advantages over previous CT based PGD, including close to real-time imaging of the irradiated dosimeter, as well as the ability to maintain the dosimeter in the same physical location for irradiation and imaging, thereby eliminating spatial errors due to dosimeter re-positioning for read-out that may occur for other systems. However the dosimetric characteristics of a LI-CBCT PGD system remain to be established. The work herein determines the dosimetric properties and critical parameters needed to perform cone beam PGD. In particular, we show that imaging the dosimeter 20-30 min post irradiation offers excellent recovery of maximum polymerization yield ([Formula: see text]90%), averaging with as few as 10 image averages can provide ∼90% gamma pass rates (3%, 3 mm) as compared to treatment planning, and that eliminating outlier averaging points can improve the precision and signal to noise ratio of resultant images. In summary, with appropriate methodology LI-CBCT PGD can provide dosimetric data capable of verification of complex high dose radiation deliveries in three dimensions and may find use in commissioning and validation of novel complex treatments.


Assuntos
Tomografia Computadorizada de Feixe Cônico , Aceleradores de Partículas , Radiometria/instrumentação , Géis , Humanos , Imagens de Fantasmas , Polímeros/química , Radiocirurgia/métodos , Razão Sinal-Ruído
11.
Phys Med Biol ; 65(21): 215026, 2020 11 05.
Artigo em Inglês | MEDLINE | ID: mdl-33151909

RESUMO

In this paper, we propose a method for compositing a synthetic mammogram (SM) from digital breast tomosynthesis (DBT) slice images. The method consists of four parts. The first part is image reconstruction of DBT from the acquired projection data by use of backprojection-filtration (BPF) algorithm with a low-frequency boosting scheme and a high-density object reduction technique embedded. Also, a few expectation-maximization (EM) iterations have been additively implemented on top of the BPF algorithm to prepare a separate volume image. The second is generating three kinds of intermediate SMs. A forward projection image and a linear structure weighted forward projection image were computed. A maximum intensity projection of the BPF reconstructed volume image was also generated. The third part is integrating three intermediate SMs. The last is the post-processing of the SM. We scanned two physical phantoms in a prototype DBT scanner, and we have evaluated the performance of the proposed method. We also performed a clinical data study by use of 30 patient data who went through both DBT and digital mammography (DM) scans. Three experienced radiologists have read the SMs generated by several component techniques and also read the DM of each patient, and evaluated the generated SMs. The experimental phantom study and the clinical reader study consistently demonstrated the usefulness of the proposed method.


Assuntos
Artefatos , Processamento de Imagem Assistida por Computador/métodos , Mamografia , Intensificação de Imagem Radiográfica/métodos , Algoritmos , Neoplasias da Mama/diagnóstico por imagem , Feminino , Humanos , Imagens de Fantasmas , Razão Sinal-Ruído
12.
Sci Rep ; 10(1): 19196, 2020 11 05.
Artigo em Inglês | MEDLINE | ID: mdl-33154542

RESUMO

Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVID19) pneumonia. We aimed to construct a system based on deep learning for detecting COVID-19 pneumonia on high resolution CT. For model development and validation, 46,096 anonymous images from 106 admitted patients, including 51 patients of laboratory confirmed COVID-19 pneumonia and 55 control patients of other diseases in Renmin Hospital of Wuhan University were retrospectively collected. Twenty-seven prospective consecutive patients in Renmin Hospital of Wuhan University were collected to evaluate the efficiency of radiologists against 2019-CoV pneumonia with that of the model. An external test was conducted in Qianjiang Central Hospital to estimate the system's robustness. The model achieved a per-patient accuracy of 95.24% and a per-image accuracy of 98.85% in internal retrospective dataset. For 27 internal prospective patients, the system achieved a comparable performance to that of expert radiologist. In external dataset, it achieved an accuracy of 96%. With the assistance of the model, the reading time of radiologists was greatly decreased by 65%. The deep learning model showed a comparable performance with expert radiologist, and greatly improved the efficiency of radiologists in clinical practice.


Assuntos
Infecções por Coronavirus/complicações , Aprendizado Profundo , Processamento de Imagem Assistida por Computador/métodos , Pneumonia Viral/complicações , Pneumonia/complicações , Pneumonia/diagnóstico por imagem , Razão Sinal-Ruído , Tomografia Computadorizada por Raios X , Adulto , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Estudos Retrospectivos
13.
Nat Commun ; 11(1): 5550, 2020 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-33144563

RESUMO

The capabilities of imaging technologies, fluorescent sensors, and optogenetics tools for cell biology are advancing. In parallel, cellular reprogramming and organoid engineering are expanding the use of human neuronal models in vitro. This creates an increasing need for tissue culture conditions better adapted to live-cell imaging. Here, we identify multiple caveats of traditional media when used for live imaging and functional assays on neuronal cultures (i.e., suboptimal fluorescence signals, phototoxicity, and unphysiological neuronal activity). To overcome these issues, we develop a neuromedium called BrainPhys™ Imaging (BPI) in which we optimize the concentrations of fluorescent and phototoxic compounds. BPI is based on the formulation of the original BrainPhys medium. We benchmark available neuronal media and show that BPI enhances fluorescence signals, reduces phototoxicity and optimally supports the electrical and synaptic activity of neurons in culture. We also show the superior capacity of BPI for optogenetics and calcium imaging of human neurons. Altogether, our study shows that BPI improves the quality of a wide range of fluorescence imaging applications with live neurons in vitro while supporting optimal neuronal viability and function.


Assuntos
Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Diagnóstico por Imagem , Neurônios/fisiologia , Optogenética , Potenciais de Ação/fisiologia , Animais , Sobrevivência Celular , Células Cultivadas , Líquido Cefalorraquidiano/metabolismo , Meios de Cultura , Fluorescência , Humanos , Células-Tronco Pluripotentes Induzidas/citologia , Células-Tronco Pluripotentes Induzidas/metabolismo , Luz , Rede Nervosa/fisiologia , Concentração Osmolar , Ratos , Razão Sinal-Ruído , Sinapses/fisiologia
14.
Nihon Hoshasen Gijutsu Gakkai Zasshi ; 76(11): 1143-1151, 2020.
Artigo em Japonês | MEDLINE | ID: mdl-33229844

RESUMO

PURPOSE: It is well known that there is a trade-off relationship between image noise and exposure dose in X-ray computed tomography (CT) examination. Therefore, CT dose level was evaluated by using the CT image noise property. Although noise power spectrum (NPS) is a common measure for evaluating CT image noise property, it is difficult to evaluate noise performance directly on clinical CT images, because NPS requires CT image samples with uniform exposure area for the evaluation. In this study, various noise levels of CT phantom images were classified for estimating dose levels of CT images using convolutional neural network (CNN). METHOD: CT image samples of water phantom were obtained with a combination of mAs value (50, 100, 200 mAs) and X-ray tube voltage (80, 100, 120 kV). The CNN was trained and tested for classifying various noise levels of CT image samples by keeping 1) a constant kV and 2) a constant mAs. In addition, CT dose levels (CT dose index: CTDI) for all exposure conditions were estimated by using regression approach of the CNN. RESULT: Classification accuracies for various noise levels were very high (more than 99.9%). The CNN-estimated dose level of CT images was highly correlated (r=0.998) with the actual CTDI. CONCLUSION: CT image noise level classification using CNN can be useful for the estimation of CT radiation dose.


Assuntos
Redes Neurais de Computação , Tomografia Computadorizada por Raios X , Imagens de Fantasmas , Doses de Radiação , Razão Sinal-Ruído
15.
Ann Nucl Med ; 34(12): 884-891, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33141408

RESUMO

OBJECTIVE: 18F is the most extensively used radioisotope in current clinical practices of PET imaging. This selection is based on the several criteria of pure PET radioisotopes with an optimum half-life, and low positron energy that contributes to a smaller positron range. In addition to 18F, other radioisotopes such as 68Ga and 124I are currently gained much attention with the increase in interest in new PET tracers entering the clinical trials. This study aims to determine the minimal scan time per bed position (Tmin) for the 124I and 68Ga based on the quantitative differences in PET imaging of 68Ga and 124I relative to 18F. METHODS: The European Association of Nuclear Medicine (EANM) procedure guidelines version 2.0 for FDG-PET tumor imaging has adhered for this purpose. A NEMA2012/IEC2008 phantom was filled with tumor to background ratio of 10:1 with the activity concentration of 30 kBq/ml ± 10 and 3 kBq/ml ± 10% for each radioisotope. The phantom was scanned using different acquisition times per bed position (1, 5, 7, 10 and 15 min) to determine the Tmin. The definition of Tmin was performed using an image coefficient of variations (COV) of 15%. RESULTS: Tmin obtained for 18F, 68Ga and 124I were 3.08, 3.24 and 32.93 min, respectively. Quantitative analyses among 18F, 68Ga and 124I images were performed. Signal-to-noise ratio (SNR), contrast recovery coefficients (CRC), and visibility (VH) are the image quality parameters analysed in this study. Generally, 68Ga and 18F gave better image quality as compared to 124I for all the parameters studied. CONCLUSION: We have defined Tmin for 18F, 68Ga and 124I SPECT CT imaging based on NEMA2012/IEC2008 phantom imaging. Despite the long scanning time suggested by Tmin, improvement in the image quality is acquired especially for 124I. In clinical practice, the long acquisition time, nevertheless, may cause patient discomfort and motion artifact.


Assuntos
Elementos Radioativos/química , Marcação por Isótopo/métodos , Neoplasias/diagnóstico por imagem , Tomografia Computadorizada com Tomografia por Emissão de Pósitrons/instrumentação , Tomografia Computadorizada com Tomografia por Emissão de Pósitrons/métodos , Composição de Medicamentos , Radioisótopos de Flúor/química , Radioisótopos de Gálio/química , Humanos , Processamento de Imagem Assistida por Computador/instrumentação , Processamento de Imagem Assistida por Computador/métodos , Radioisótopos do Iodo/química , Imagens de Fantasmas , Doses de Radiação , Traçadores Radioativos , Razão Sinal-Ruído , Fatores de Tempo
16.
Medicine (Baltimore) ; 99(47): e23138, 2020 Nov 20.
Artigo em Inglês | MEDLINE | ID: mdl-33217817

RESUMO

We have developed a deep learning-based approach to improve image quality of single-shot turbo spin-echo (SSTSE) images of female pelvis. We aimed to compare the deep learning-based single-shot turbo spin-echo (DL-SSTSE) images of female pelvis with turbo spin-echo (TSE) and conventional SSTSE images in terms of image quality.One hundred five and 21 subjects were used as training and test sets, respectively. We performed 6-fold cross validation. In the training process, low-quality images were generated from TSE images as input. TSE images were used as ground truth images. In the test process, the trained convolutional neural network was applied to SSTSE images. The output images were denoted as DL-SSTSE images. Apart from DL-SSTSE images, classical filtering methods were adopted to SSTSE images. Generated images were denoted as F-SSTSE images. Contrast ratio (CR) of gluteal fat and myometrium and signal-to-noise ratio (SNR) of gluteal fat were measured for all images. Two radiologists graded these images using a 5-point scale and evaluated the image quality with regard to overall image quality, contrast, noise, motion artifact, boundary sharpness of layers in the uterus, and the conspicuity of the ovaries. CRs, SNRs, and image quality scores were compared using the Steel-Dwass multiple comparison tests.CRs and SNRs were significantly higher in DL-SSTSE, F-SSTSE, and TSE images than in SSTSE images. Scores with regard to overall image quality, contrast, noise, and boundary sharpness of layers in the uterus were significantly higher on DL-SSTSE and TSE images than on SSTSE images. There were no significant differences in the CRs, SNRs, and respective scores between DL-SSTSE and TSE images. The score with regard to motion artifacts was significantly higher on DL-SSTSE, F-SSTSE, and SSTSE images than on TSE images. The score with regard to the conspicuity of ovaries was significantly higher on DL-SSTSE images than on F-SSTSE, SSTSE, and TSE images (P < .001).DL-SSTSE images showed higher image quality as compared with SSTSE images. In comparison with conventional TSE images, DL-SSTSE images had acceptable image quality while keeping the advantage of the motion artifact-robustness and acquisition time efficiency in SSTSE imaging.


Assuntos
Imagem por Ressonância Magnética/métodos , Redes Neurais de Computação , Pelve/diagnóstico por imagem , Melhoria de Qualidade , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Razão Sinal-Ruído
17.
J Vis Exp ; (164)2020 10 31.
Artigo em Inglês | MEDLINE | ID: mdl-33191931

RESUMO

Synapses are the functional elements of neurons and their defects or losses are at the basis of several neurodegenerative and neurological disorders. Imaging studies are widely used to investigate their function and plasticity in physiological and pathological conditions. Because of their size and structure, localization studies of proteins require high-resolution imaging techniques. In this protocol, we describe a procedure to study in primary neurons the co-localization of target proteins with synaptic markers at a super-resolution level using structured illumination microscopy (SIM). SIM is a patterned-light illumination technique that doubles the spatial resolution of wide-field microscopy, reaching a detail of around 100 nm. The protocol indicates the required controls and settings for robust co-localization studies and an overview of the statistical methods to analyze the imaging data properly.


Assuntos
Microscopia/métodos , Neurônios/citologia , Neurônios/metabolismo , Razão Sinal-Ruído , Sinapses/metabolismo , Biomarcadores/metabolismo , Imageamento Tridimensional , Transporte Proteico
18.
Sci Rep ; 10(1): 16487, 2020 10 05.
Artigo em Inglês | MEDLINE | ID: mdl-33020508

RESUMO

The Italian Government has decreed a series of progressive restrictions to delay the COVID-19 pandemic diffusion in Italy since March 10, 2020, including limitation in individual mobility and the closure of social, cultural, economic and industrial activities. Here we show the lockdown effect in Northern Italy, the COVID-19 most affected area, as revealed by noise variation at seismic stations. The reaction to lockdown was slow and not homogeneous with spots of negligible noise reduction, especially in the first week. A fresh interpretation of seismic noise variations in terms of socio-economic indicators sheds new light on the lockdown efficacy pointing to the causes of such delay: the noise reduction is significant where non strategic activities prevails, while it is small or negligible where dense population and strategic activities are present. These results are crucial for the a posteriori interpretation of the pandemic diffusion and the efficacy of differently targeted political actions.


Assuntos
Infecções por Coronavirus/epidemiologia , Terremotos/estatística & dados numéricos , Pneumonia Viral/epidemiologia , Quarentena/estatística & dados numéricos , Infecções por Coronavirus/prevenção & controle , Humanos , Itália , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Razão Sinal-Ruído , Tempo
19.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3090-3093, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018658

RESUMO

Steady State Visual Evoked Potentials (SSVEPs) have been widely used in Brain-Computer Interfaces (BCIs). SSVEP-BCIs have advantages of high classification accuracy, high information transfer rate, and strong anti-interference ability. Traditional studies mostly used low/medium frequency SSVEPs as system control signals. However, visual flickers with low/medium frequencies are uncomfortable, and even cause visual fatigue and epilepsy seizure. High-frequency SSVEP is a promising approach to solve these problems, but its miniature amplitude and low signal-to-noise ratio (SNR) would pose great challenges for target recognition. This study developed an innovative BCI paradigm to enhance the SNR of high-frequency SSVEP, which is named Steady-State asymmetrically Visual Evoked Potential (SSaVEP). Ten characters were encoded by ten couples of asymmetric flickers whose durations only lasted one second and frequencies ranged from 31 to 40 Hz with a step of 1 Hz. Discriminative canonical pattern matching (DCPM) was used to decode the high-frequency SSaVEP signals. Four subjects participated in the offline experiment. As a result, the accuracy achieved an average of 87.5% with a peak of 97.1%. The simulated online information transfer rate reached 87.2 bits/min on average and 111.2 bits/min for maximum. The results of this study demonstrate the high-frequency SSaVEP paradigm is a promising approach to alleviate the discomfort caused by visual stimuli and thereby can broaden the applications of BCIs.


Assuntos
Interfaces Cérebro-Computador , Potenciais Evocados Visuais , Eletroencefalografia , Humanos , Fenômenos Físicos , Razão Sinal-Ruído
20.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3415-3419, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018737

RESUMO

Magnetomyography (MMG) is the measurement of magnetic signals generated in the skeletal muscle of humans by electrical activities. However, current technologies developed to detect such tiny magnetic field are bulky, costly and require working at the temperature-controlled environment. Developing a miniaturized, low cost and room temperature magnetic sensors provide an avenue to enhance this research field. Herein, we present an integrated tunnelling magnetoresistive (TMR) array for room temperature MMG applications. TMR sensors were developed with low-noise analogue front-end circuitry to detect the MMG signals without and with averaging at a high signal-to-noise ratio. The MMG was achieved by averaging signals using the Electromyography (EMG) signal as a trigger. Amplitudes of 200 pT and 30 pT, corresponding to periods when the hand is tense and relaxed, were observed, which is consistent with muscle simulations based on finite-element method (FEM) considering the effect of distance from the observation point to the magnetic field source.


Assuntos
Campos Magnéticos , Músculo Esquelético , Eletromiografia , Humanos , Magnetismo , Razão Sinal-Ruído
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