RESUMO
Background noise in many fields such as medical imaging poses significant challenges for accurate diagnosis, prompting the development of denoising algorithms. Traditional methodologies, however, often struggle to address the complexities of noisy environments in high dimensional imaging systems. This paper introduces a novel quantum-inspired approach for image denoising, drawing upon principles of quantum and condensed matter physics. Our approach views medical images as amorphous structures akin to those found in condensed matter physics and we propose an algorithm that incorporates the concept of mode resolved localization directly into the denoising process. Notably, our approach eliminates the need for hyperparameter tuning. The proposed method is a standalone algorithm with minimal manual intervention, demonstrating its potential to use quantum-based techniques in classical signal denoising. Through numerical validation, we showcase the effectiveness of our approach in addressing noise-related challenges in imaging and especially medical imaging, underscoring its relevance for possible quantum computing applications.
RESUMO
Background noise in many fields such as medical imaging poses significant challenges for accurate diagnosis, prompting the development of denoising algorithms. Traditional methodologies, however, often struggle to address the complexities of noisy environments in high dimensional imaging systems. This paper introduces a novel quantum-inspired approach for image denoising, drawing upon principles of quantum and condensed matter physics. Our approach views medical images as amorphous structures akin to those found in condensed matter physics and we propose an algorithm that incorporates the concept of mode resolved localization directly into the denoising process. Notably, our approach eliminates the need for hyperparameter tuning. The proposed method is a standalone algorithm with minimal manual intervention, demonstrating its potential to use quantum-based techniques in classical signal denoising. Through numerical validation, we showcase the effectiveness of our approach in addressing noise-related challenges in imaging and especially medical imaging, underscoring its relevance for possible quantum computing applications.
RESUMO
Due to the expansion of the aquaculture industry in the world and the importance of controlling ammonia in fish breeding water, high levels of which impose significant damage to fish farming, it is crucial to develop affordable, rapid, and on-site methods for timely and accurate detection of ammonia. In this study, a colorimetric sensor based on the formation of gold/silver core/shell nanorods (NRs) was developed for the rapid detection of ammonia. The sensor functioned by the specific dissolution of silver(i) oxide by ammonia, which triggered the activation of silver ions and the subsequent formation of gold/silver core/shell NRs in the presence of a reducing agent (i.e., ascorbic acid (AA)). This led to changes in the surface composition, size, and aspect ratio of the NRs, which was accompanied by a vivid color change from green to red/orange in less than a minute. The colorimetric sensor was optimized by adjusting the effective parameters, including ascorbic acid, silver ion, and sodium hydroxide concentration as well as pH and reaction time. After the optimization process, the sensor was found to have a linear range from 50 to 800 µmol L-1 (0.85-13.6 ppm). In addition, the application of the sensor was validated by measuring the ammonia content in water samples from rearing ponds for rainbow trout, sturgeon, and tilapia before and after feeding. The sensor's label-free, rapid, user-friendly, naked-eye, and cost-effective operation makes it an attractive option for on-site environmental monitoring of ammonia.
RESUMO
This meta-analysis aimed to evaluate the effects of flaxseed supplementation on weight loss, lipid profiles, high-sensitivity C-reactive protein (hs-CRP), and glucose levels in patients with coronary artery disease (CAD). A systematic search was performed using various online databases, including Scopus, PubMed, Web of Science, EMBASE, and Cochrane Library, to identify relevant randomized controlled trials (RCTs) until June 2023. To evaluate heterogeneity among the selected studies, the Q-test and I2 statistics were employed. Data were combined using either a fixed- or random-effects model and presented as a weighted mean difference (WMD) with a 95% confidence interval (CI). Of the 428 citations, six RCTs were included. The pooled results did not show significant changes in the WMD of lipid factors (high-density lipoprotein cholesterol, triglycerides (TG), low-density lipoprotein cholesterol, and total cholesterol) following flaxseed intake. However, after performing a sensitivity analysis to determine the source of heterogeneity, flaxseed supplementation resulted in a significant decrease in TG levels (WMD = -18.39 mg/dL; 95% CI: -35.02, -1.75). Moreover, no significant differences were observed in either weight or BMI following flaxseed intake. However, the circulating levels of fasting blood glucose (WMD = -8.35 mg/dL; 95% CI: -15.01, -1.69, p = .01) and hs-CRP (WMD = -1.35 mg/L; 95% CI: -1.93, -0.77, p < .01) significantly decreased after the intervention. Flaxseed supplementation was associated with lowering FBS, hs-CRP, and TG levels but did not affect weight loss parameters and other lipid markers in CAD.
Assuntos
Doença da Artéria Coronariana , Linho , Humanos , Proteína C-Reativa , Glucose , Ensaios Clínicos Controlados Aleatórios como Assunto , HDL-Colesterol , Redução de Peso , Suplementos NutricionaisRESUMO
The Dynamic Cardiac SPECT (DC-SPECT) system is being developed at the Massachusetts General Hospital, featuring a static cardio focus asymmetrical geometry enabling simultaneous high-resolution and high-sensitivity imaging. Among 14 design iterations of the DC-SPECT with varying number of detector heads, system sensitivity and resolution, the current version under development features 10 mm FWHM geometrical resolution (without resolution recovery) and 0.07% sensitivity at the center of the FOV, this is 1.5× resolution gain and 7× sensitivity gain compared to a conventional dual head gamma camera (0.01% sensitivity and 15-mm resolution). This work presents improvement in imaging resolution by implementing a spatially variant point spread function (SV-PSF) with list mode MLEM reconstruction. A resolution recovery method by PSF deconvolution is validated on list mode MLEM reconstruction for the DC-SPECT. A spatial invariant PSF is included as an additional test to show the influence of the PSF modelling accuracy on reconstructed image quality. We compare the MLEM reconstruction with and without PSF deconvolution; an analytic model is used for the calculation of system response, and the results are compared to the reconstruction with system modelling using Monte Carlo (MC) based methods. Results show that with PSF modelling applied, the quality of the reconstructed image is improved, and the DC-SPECT system can achieve a 4.5 mm central spatial resolution with average 795 counts/Mbq. Both the SV-PSF and the spatial-invariant PSF improve the image quality, and the reconstruction with SV-PSF generates line profiles closer to the ground truth. The results show substantial improvement over the GE Discovery 570c performance (7 mm spatial resolution with an average 460 counts/MBq, 5.8 mm resolution at the FOV center). The impact of PSF deconvolution is significant, improvement of the reconstructed image quality is evident in comparison to MC simulated system matrix with the same sampling size in the simulation.
Assuntos
Algoritmos , Processamento de Imagem Assistida por Computador , Processamento de Imagem Assistida por Computador/métodos , Imagens de Fantasmas , Tomografia Computadorizada de Emissão de Fóton Único/métodos , Tomografia por Emissão de Pósitrons/métodosRESUMO
This work highlights the significance of equivariant networks as efficient and high-performance approaches for tomography applications. Our study builds upon the limitations of conventional Convolutional Neural Networks (CNNs), which have shown promise in post-processing various medical imaging systems. However, the efficiency of conventional CNNs heavily relies on an undiminished and proper training set. To tackle this issue, in this study, we introduce an equivariant network, aiming to reduce CNN's dependency on specific training sets. We evaluate the efficacy of equivariant spherical CNNs (SCNNs) for 2- and 3-dimensional medical imaging problems. Our results demonstrate superior quality and computational efficiency of SCNNs in denoising and reconstructing benchmark problems. Furthermore, we propose a novel approach to employ SCNNs as a complement to conventional image reconstruction tools, enhancing the outcomes while reducing reliance on the training set. Across all cases, we observe a significant decrease in computational costs while maintaining the same or higher quality of image processing using SCNNs compared to CNNs. Additionally, we explore the potential of this network for broader tomography applications, particularly those requiring omnidirectional representation.
RESUMO
Biophotonic imaging has revolutionized the operation room by providing surgeons intraoperative image-guidance to diagnose tumors more efficiently and to resect tumors with real-time image navigation. Among many medical imaging modalities, near-infrared (NIR) light is ideal for image-guided surgery because it penetrates relatively deeply into living tissue, while nuclear imaging provides quantitative and unlimited depth information. It is therefore ideal to develop an integrated imaging system by combining NIR fluorescence and gamma-positron imaging to provide surgeons with highly sensitive and quantitative detection of diseases, such as cancer, in real-time without changing the look of the surgical field. The focus of this review is to provide recent progress in intraoperative biophotonic imaging systems, NIR fluorescence imaging and intraoperative nuclear imaging devices, and their future perspectives for image-guided interventions.
RESUMO
We are using the Laser Induced Optical Barriers (LIOB) technique to fabricate scintillator detectors with combined performance characteristics of the two standard detector types, mechanically pixelated arrays and monolithic crystals. This is done by incorporation of so-called optical barriers that have a refractive index lower than that of the crystal bulk. Such barriers can redirect the scintillation light and allow for control of the light spread in the detector. Previous work has shown that the LIOB technique has the potential to achieve detectors with high transversal and depth of interaction (DOI) resolution simultaneously in a single-side readout configuration, suitable for high resolution PET imaging. However, all designs studied thus far present edge effect issues similarly as in the standard detector categories. In this work we take advantage of the inherent flexibility of the LIOB technique and investigate alternative barrier patterns with the aim to address this problem. Light transport simulations of barrier patterns in LYSO:Ce, with deeper barrier walls moving towards the detector edge show great promise in reducing the edge effect, however there is a trade-off in terms of achievable DOI information. Furthermore, fabrication and characterization of a 20 mm thick LYSO:Ce detector with optical barriers forming a pattern of 1 × 1 × 20mm3 pixel like structures show that light channeling in laser-processed detectors in agreement with optical barriers with refractive index between 1.2 and 1.4 is achievable.
RESUMO
NeuroPET is a cylindrical full ring mobile PET/CT scanner for brain imaging that was developed by Photo Diagnostic Systems, Inc. The scanner has 7 modules, each with 3×4 detector blocks. The detectors have two layers of scintillator arrays with a half pixel pitch offset to realize two levels of depth of interaction. In this study, we evaluated the NeuroPET scanner modeled in the GATE simulation tool and analyzed the acquired data to better understand the contribution of inter-detector scattering (IDS). The results show that the average difference between simulated and measured data for a point-like source is 2.5%. The differences are 4.7% and 2.7% for NEMA line source in two data acquisition modes and 5.5% for peak NECR measurement. IDS evaluation indicated that the total fractions of the cross-layer crystal scatter (CLCS) and inter-layer crystal scatter (ILCS) events in singles detection mode are 1.98% and 7.98%, respectively. Approximately 90% of these CLCS events deposit most of their energy in the crystal layer other than the layer of first interaction. Additionally, no significant difference in ILCS fractions between the two layers (8.05% vs 7.35%) was observed. The simulation results demonstrate that ILCS events account for â¼79% of the total mis-positioned events.
Assuntos
Encéfalo/diagnóstico por imagem , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Humanos , Modelos Teóricos , Imagens de FantasmasRESUMO
PURPOSE: We developed a high performance portable gamma camera platform dedicated to identification of sentinel lymph nodes (SLNs) and radio-guided surgery for cancer patients. In this work, we present the performance characteristics of SURGEOSIGHT-I, the first version of this platform that can intra-operatively provide high-resolution images of the surveyed areas. METHODS: At the heart of this camera, there is a 43×43 array of pixelated sodium-activated cesium iodide (CsI(Na)) scintillation crystal with 1×1mm(2) pixel size and 5mm thickness coupled to a Hamamatsu H8500 flat-panel multi-anode (64 channels) photomultiplier tube. The probe is equipped with a hexagonal parallel-hole lead collimator with 1.2mm holes. The detector, collimator, and the associated front-end electronics are encapsulated in a common housing referred to as head. RESULTS: Our results show a count rate of â¼41kcps for 20% count loss. The extrinsic energy resolution was measured as 20.6% at 140keV. The spatial resolution and the sensitivity of the system on the collimator surface was measured as 2.2mm and 142cps/MBq, respectively. In addition, the integral and differential uniformity, after uniformity correction, in useful field-of-view (UFOV) were measured 4.5% and 4.6%, respectively. CONCLUSIONS: This system can be used for a number of clinical applications including SLN biopsy and radiopharmaceutical-guided surgery.