Abstract:Objective:To explore the application value of virtual monochromatic imaging(VMI)technology with dual-layer detector spectral computed tomography(CT)in temporal bone CTV imaging.Methods:A retrospective analysis was performed on the imaging data of 44 patients who underwent temporal bone CT angiography and venography(CTA+CTV)examinations using Philips IQon CT.The data included conventional 140 kVp images from the CTV scanning sequence and 10 groups of virtual monochromatic images(40-120 keV at 10 keV intervals)reconstructed from the spectral data.For each group of images,the CT values of venous vessels in the confluence sinuum region were measured along with the CT values and standard deviation(SD)of the adjacent parenchyma at the same level.The signal-to-noise ratio(SNR)and contrast-to-noise ratios(CNR)were calculated.Two experienced radiologists scored and compared the multiplanar reconstruction(MPR)and cerebral vascular intensity projection(CIP)images.Results:With an increase in the monochromatic energy level,the SNR,CNR,vascular CT,and SD values of the images decreased,with the VMI groups showing statistically significant differences with respect to the other groups.In the subjective evaluation of the MPR images,no statistically significant differences were observed between the scores of the conventional 140 kVp images and those of the 80 keV and 90 keV groups.Among them,the 50 keV VMI group achieved the highest MPR image score of 5(4,5).In the subjective evaluation of CIP images,there was no statistically significant difference between the scores of the conventional 140 kVp images and those of the 80 keV VMI group.All images in the 40,50,and 60 keV VMIs groups met the diagnostic requirements,and their subjective scores were superior to those of the other groups,with scores of 3(3,3).No statistically significant differences were observed among the three groups.Conclusion:Virtual monochromatic images at(80～90)keV VMIs using dual-layer detector spectral CT were comparable to the 140 kVp images.VMIs with energy levels below 70 keV can effectively improve the visualization of venous vessels.Conventional 50 keV VMI is recommended as the optimal imaging modality for diagnosis.

Abstract:Objective:To investigate the value of virtual monoenergetic images(VMI)in dual-energy CT(DECT)for optimizing peripancreatic vein imaging.Methods:Dual-energy CT enhanced scans(100 kV/Sn 150 kV)of 65 patients with pancreatic ductal adenocarcinoma(PDAC)and 60 healthy controls were retrospectively analyzed,and portal stage images were reconstructed at 45 keV monoenergetic and linear fusion reconstruction with a weight factor of M0.6.CT values of the pancreatic parenchyma,portal vein trunk,superior mesenteric vein,and subcutaneous fat were measured.Additionally,the signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR),and standard deviation(SD)of the CT values of subcutaneous fat were calculated.The diameters of the posterior superior pancreaticoduodenal vein(PSPDV),anterior superior pancreaticoduodenal vein(ASPDV),and gastrocolic trunk(GCT)were measured,and the display effect of these vessels was evaluated using the five-point method.Results:The CT values,SNR,and CNR of each blood vessel and pancreatic parenchyma on 45 keV VMI were significantly higher than those on linear fusion images(PEI).The image noise of 45 keV VMI was significantly higher than that of PEI.The peripancreatic venule score on 45 keV VMI was significantly higher than that on PEI.In the PDAC group,excluding pancreatic tail tumors,there were 44 cases of non-resectable tumors.Twenty patients had peripancreatic small vein dilatation,accounting for 45%of non-resectable tumors;16 patients had resectable tumors;and two patients had peripancreatic small vein dilatation,accounting for 12.5%of resectable tumors.A statistical correlation may exist between peripancreatic small vein dilatation and PDAC resectability.In the control group,three patients had peripancreatic small vein dilatation.This suggests a statistical correlation between peripancreatic small vein dilatation and PDAC positivity.Conclusion:Compared with PEI,DECT 45 keV VMI can significantly enhance imaging of peripancreatic veins,and the dilatation of peripancreatic venules can serve as an important reference for unresectable PDAC.

Abstract:While the Ordos Basin is recognized for its substantial hydrocarbon exploration prospects,its rugged loess tableland terrain has rendered seismic exploration exceptionally challenging[1-3].Persistent obstacles such as complex 3D survey planning,low signal-to-noise ratio raw data,inadequate near-surface velocity modeling,and imaging inaccuracy have long hindered the advancement of seismic exploration across this region.Through a problem-solving approach rooted in geological target analysis,this research systematically investigates the behavioral patterns of nodal seismometer-based high-density seismic acquisition in loess plateau.Tailored advancements in waveform enhancement and depth velocity modelling methodologies have been engineered.Field validations confirm that the optimized workflow demonstrates marked improvements in amplitude preservation and imaging resolution,offering novel insights for future reservoir characterization endeavors.

Abstract:Objective:This study investigates the effects of different scanning modes and noise index(NI)on inner ear computed tomography(CT)image quality and radiation dose.Methods:(1)Head anthropomorphs phantoms were scanned using a 64-slice helical CT scanner.Both Axial and Helical scanning modes were employed,with each mode using progressively increasing NI values(3-6,totaling 21 values).In the Helical mode,each NI value was used to reconstruct images in two modes:Conventional Helical reconstruction and Helical reconstruction with spiral artifact correction(IQE).Three groups of images were obtained,each comprising 63 sequential images collected and reconstructed.Axial scanning was performed with a rotational speed of 1 second,a Helical scanning pitch of 0.531︰1,and a speed of 1 second,whereas the other scanning parameters remained constant.(2)Volume CT dose index(CTDIvol)and dose-length product(DLP)were recorded under different scanning conditions to analyze radiation dose.(3)Both objective and subjective image quality assessments were performed.Objective evaluations were conducted on three image groups,calculating the signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR),and figure of merit(FOM)for the region of interest(ROI).Subjective evaluations included assessments of image edge contrast,image intensity,axial noise and artifacts,and multiplanar reconstruction(MPR)quality;a double-blinded method with a 5-point scale was used.The optimal NI value was determined based on the FOM values and subjective image quality assessments.Results:(1)In both Axial and Helical scanning modes,CTDIvol and DLP decreased as NI values increased.No significant difference was observed in CTDIvol,but a significant difference was noted in DLP(2)Statistically significant differences were observed in soft tissue SNR,as well as SNR,CNR,and FOM for bone tissue,between Axial and Helical conventional modes and IQE mode,Axial imaging with an NI of 4.7 yielded optimal FOM and subjective evaluation scores.Conclusion:For inner ear CT scanning(range≤4 mm)using a 64-row CT scanner,MPR reconstruction without fault artifacts can be achieved by obtaining thin-layer images through single-layer scanning without bed movement.Considering that the radiation dose and image quality are better than those of conventional spiral scans or even IQE scans,MPR reconstruction without fault artifacts can be performed using 64-row CT.The recommended NI setting for inner ear imaging is 4.7,as it provides satisfactory image quality while minimizing radiation exposure.

Abstract:Coronary computed tomography angiography-derived fractional flow reserve(CT-FFR)offers comprehensive assessment by providing both morphological and functional information from a single coronary computed tomography angiography(CCTA)scan.Its clinical application and research have gained considerable attention.This paper reviews the technical principles,clinical applications,and future prospects of CT-FFR.

Abstract:Objective:To explore the feasibility of the SEMI mode of the intelligent optimal tube voltage selection technique(Care kV SEMI)in combination with an iterative algorithm in low-dose calcium score scanning for coronary artery examination.Methods:SEMI mode of Care kV and tube current modulation(CareDose 4D)were used in the phantom experiment.For the SEMI group SEMI 120 kV(ref.kV was 100 and 120 kV),ref.mAs was 40,60,and 80 mAs.The reconstruction algorithms were filtered back projection(FBP)ADMIRE 3,4,5.The volume CT dose index(CTDIvol),contrast-to-noise ratio(CNRp)and figure of merit(FOM)of each group were compared,and a set of parameters were selected for clinical patient image acquisition after a comprehensive comparison.A retrospective analysis of coronary artery calcium score scanning images was conducted,using 30 patients as a control group(ref.kV,120 kV;ref.mAs,80 mAs;reconstruction algorithm,filtered back projection,FBP)and a prospective collection of 109 patients with coronary artery calcium score CT images as an experimental group(Care kV SEMI,120 kV;ref.kV,100 kV;ref.mAs,80 mAs).The reconstruction algorithms were FBP and ADMIRE 3,5.The dose length product(DLP),effective dose(ED),contrast-to-noise ratio(CNR)at the left main coronary artery(LM)and right coronary artery(RCA)ostial level,Agaston score,and risk classification were recorded and compared between groups.The images of the patients were evaluated by two senior diagnostic doctors on a four-point scale.The radiation dose,calcification score,risk classification,and image quality were statistically analyzed using SPSS software.Results:(1)Phantom experiment:The radiation dose of the experimental group was lower than that of the control group.Under the same scanning parameters,the CNRp increased with an increasing reconstruction algorithm level.The FOM of the four reconstruction algorithms in the ref.kV 100 kV+ref.mAs 80 mAs group was higher than that in the control group.(2)Clinical study:There was a statistically significant difference in ED between the experimental group and the control group.There was no statistically significant difference in CNRc between the experimental group with FBP and the control group on the LM and RCA levels.There was no significant difference in Agaston score between the experimental and control groups.The consistency of the risk grade in the experimental group was good,with kappa values of 0.93 and 0.88,respectively.There was no statistically significant difference in FBP and CNRc between the experimental and control groups at either level.The subjective evaluation results of doctors A and B were consistent,and the kappa value was 0.952.There was a statistically significant difference in the subjective evaluation between the two groups.Conclusion:Care kV SEMI combined with an iterative algorithm has little effect on the calcification score and risk classification,and it can effectively reduce the radiation doses of patients with a BMI of 18-25.

Abstract:Objective:To investigate how the weights of the deep learning-based ClearInfinity(CI)algorithm affect the quality of 55 keV virtual monoenergetic images(VMIs)in cranial spectral computed tomography angiography(CTA),and to provide a basis for clinical optimization of reconstruction parameters.Methods:A total of 38 patients who had undergone cranial spectral CTA were retrospectively enrolled.The original data were reconstructed using the CI algorithm with weights of 10%,30%,50%,70%,and 90%to obtain five groups of 55 keV VMIs.Objective evaluation was performed by measuring the vascular CT values,gray matter CT values,background noise(BN),signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR).Double-blind subjective scoring of image noise,vascular edges,and detailed display was performed by two radiologists.Results:No statistically significant differences were observed in the CT values of blood vessels(right internal carotid artery,right middle cerebral artery,and basilar artery)or gray matter among the different weights.However,pairwise comparisons showed statistically significant differences in BN,SNR,and CNR among the weight groups.BN gradually decreased,whereas SNR and CNR gradually increased with increase in algorithm weight.Subjective scores of the five groups showed statistically significant differences,with the average scores from high to low being 4.95±0.22(50%CI),4.87±0.36(70%CI),4.74±0.48(90%CI),4.66±0.58(30%CI),and 4.03±0.62(10%CI).Conclusion:The CI algorithm weight influences image quality:relatively low weights compromise image quality owing to excessive noise,whereas relatively high weights cause over-smoothing and blurring of the image,resulting in the loss of fine structures.Therefore,this study recommends a 50%CI algorithm weight for reconstructing 55 keV VMIs in cranial spectral CTA.

Abstract:Objective:To evaluate the correlation between dual-energy spectral CT(DEsCT)and CT perfusion(CTP)parameters in residual viable tumor(RVT)after transarterial chemoembolization(TACE)for hepatocellular carcinoma(HCC),and to explore the value of DEsCT in assessing the hemodynamics of RVT.Methods:78 HCC patients who underwent one-stop dual-energy spectral CT combined with low-dose CT perfusion scans 4-6 weeks after TACE were retrospectively enrolled.DEsCT parameters were measured and calculated in RVT,including arterial and portal venous phase iodine concentration(ICAP,ICPVP),normalized iodine concentration(NICAP,NICPVP),tumor iodine uptake ratio(TURAP,TURPVP),spectral curve slope(λHU AP,λHU PVP),and iodine concentration ratio(IC ratio).CTP parameters were also measured in RVT,including hepatic arterial fraction(HAF),blood flow(BF),blood volume(BV),and hepatic arterial blood flow(Hep.BF).Spearman correlation analysis was performed to assess the correlation between the two sets of parameters,with r>0.25 and P<0.05 considered statistically significant.Results:The DEsCT parameters of RVT,including ICAP,NICAP,λHU AP,TURAP,NICPVP,and IC ratio,showed good correlations with CTP parameters such as HAF,BF,and Hep.BF(0.4<r<0.9).Among them,the IC ratio exhibited the strongest correlation with HAF(r=0.868).The dose-length product(DLP)of this scanning protocol was(1 389.06±69.32)mGy·cm,and the effective radiation dose was(20.84±1.04)mSv.Conclusion:The multiparametric DEsCT parameters of RVT in HCC after TACE were significantly correlated with CTP parameters,which can serve as valuable imaging indicators reflecting the hemodynamics of RVT.

Abstract:Objective:To investigate the effect of using organ dose modulation(ODM)technology at different tube voltages on image quality and eye lens radiation dose in brain CT perfusion(CTP).Methods:Based on a clinical CTP scanning protocol,five tube voltages(70,80,100,120,and 140 kV)were used to scan a Catphan phantom and a fresh,isolated human head specimen with three tube current modulation modes:without dose modulation technology(Manual mode),with smart tube current modulation technology(Smart mA mode),and with organ dose modulation technology(ODM mode).A long rod ionization chamber was fixed at a consistent position in front of the right eye lens.Each parameter combination was scanned nine times,and the average eye lens dose(Dav)was recorded.The modulation transfer function(MTF)of the CTP528 high-contrast resolution module in the Catphan phantom was measured.In the images of the head specimen,the heads of the caudate nucleus,lenticular nucleus,and thalamus were selected as signal regions at the basal ganglia level,and the lateral ventricle,anterior limb of the internal capsule,and posterior limb of the internal capsule were selected as respective background regions to measure the contrast-to-noise ratio(CNR).The same level of brain tissue was segmented to measure three texture feature parameters:contrast,correlation,and difference variance.Two-factor analysis of variance was used to compare MTF and CNR,and multi-factor non-parametric analysis of variance was used to compare eye lens dose and texture parameters.Results:The differences in MTF across the different tube voltages were statistically significant,with MTF values positively correlated with tube voltage above 80 kV.However,there was no significant difference between different tube-current modulation modes.The CNR of each signal and background region showed significant differences among different tube voltages.The CNR for the caudate nucleus head to lateral ventricle was the largest,at 120 kV.The CNR for the lenticular nucleus/thalamus were negatively correlated with tube voltage.There were no significant differences in CNR among different tube-current modulation modes.No texture parameter was significantly associated with the tube current modulation mode.There were significant differences in Dav values with respect to both different tube voltages and tube current modulation modes.When the tube voltage was below 120 kV,the eye lens dose was negatively correlated with tube voltage,and the ODM technology reduced the eye lens dose by approximately 20%at each tube voltage.Conclusion:Employing 80～100 kV CTP scanning with organ dose modulation technology can balance image parameters and reduce radiation dose to the eye lens while ensuring adequate image quality,as recommended for clinical use.

Abstract:Objective:This study investigates the effect of a 0.312 5 mm ultra-high-resolution detector combined with a ClearInfinity(CI)deep-learning reconstruction algorithm on the image quality of orbital computed tomography(CT).Methods:Scans were performed using a NeuViz Epoch Elite CT scanner on a Catphan 600 phantom and three 7-year-old rhesus monkeys.The collimation widths were set to 64 mm×0.625 mm and 128 mm×0.312 5 mm.Images were acquired using filtered back projection(FBP),60%adaptive iterative reconstruction algorithm ClearView(CV),and 60%deep learning reconstruction algorithm CI.Image quality was evaluated using objective indicators such as the modulation transfer function(MTF)and contrast-to-noise ratio(CNR),as well as using double-blind subjective scoring.Additionally,statistical analyses were performed.Results:In phantom experiments,under standard and bone algorithms,images with a collimation width of 128×0.312 5 mm showed significantly better performances in terms of MTF50%,MTF10%,and some CNR indicators compared with those with a collimation width of 64×0.625 mm.The CNR of the CI algorithm was significantly higher than those of the FBP and CV algorithms.In animal experiments,the CNR of the medial rectus in images with a 128×0.312 5 mm collimation width was significantly higher than that in images with a 64×0.625 mm collimation width.The CI algorithm achieved the optimal CNR for the medial rectus and eyeball,as well as the highest subjective scores,with good consistency between two radiologists'subjective scores(Kappa≥0.75).Conclusion:The 0.312 5 mm ultra-high-resolution detector combined with the CI deep-learning algorithm significantly improved the resolution and contrast of orbital CT images as well as reduced noise and artifacts,thereby demonstrating promising clinical-application prospects.

Abstract:Computed tomography(CT)examination is the preferred method for the postoperative evaluation of patients with metal implants.However,some metal implants may produce artifacts in CT images,thus compromising the visualization of both the metal implants themselves and surrounding soft tissues.Furthermore,this can affect clinical diagnosis and treatment accuracy.In recent years,rapid developments in artificial intelligence have enabled deep learning reconstruction algorithms that have offered new solutions for reducing metal artifacts and have shown great promise.This paper reviews the research progress of deep learning reconstruction algorithms in reducing metal artifacts,with the aim of reducing a impact and support accurate clinical diagnosis and treatment.

Abstract:Strata calibration is the foundation of stratigraphic interpretation and reservoir analysis.Currently used calibration methods qualitatively compare geological interfaces with wave peaks,troughs,and other features,thus emphasizing the depth-time relationship of geological interfaces.These methods associate geological interfaces with specific wave peaks,troughs,or zero-crossing points but fail to reflect lateral changes in stratigraphy.This results in significant errors and insufficient interpretation.The present study proposes a method for calculating the contribution ratio of the reflection coefficients.Based on the calibration of the synthetic seismic records,the reflection coefficient sequence of the geological interfaces was computed using sonic travel time and density curves from well logging.Subsequently,the contribution ratio of each reflection coefficient to the specified wave peaks or troughs was calculated based on the seismic waveforms.This established a quantitative relationship between the seismic waveforms and the composition of the reflection coefficients and their amplitude contributions.Through the analysis of this quantitative relationship,a correspondence between geological interfaces and wave peaks or troughs with well seismic traces was established.The target stratigraphic level in the seismic data was then correlated with the reflection interface that had the maximum contribution ratio to determine the sensitive phase corresponding to the stratigraphic boundary interface.By selecting the sensitive phase,it was possible to track and analyze the lateral variations in the target stratigraphic level and lithology more accurately.The application of this method to the Shasan Lower Sandstone of the Shengtuo exploration area in the Shengli Oilfield improved the accuracy of sandbody interpretation,increasing the drilling matching rates from 75%to 92%.This indicates a broad potential applicability of the proposed method for the seismic interpretation of reservoir development.

Abstract:Objective:This study aimed to investigate the effect of ultra-high-resolution(UHR)detector computed tomography(CT)combined with a deep learning reconstruction algorithm(ClearInfinity(CI))on cranial CT image quality and its potential for radiation dose reduction.Methods:A NeuViz Epoch Elite CT scanner was used to scan a Catphan 600 phantom(with volume CT dose index(CTDIvol)set to 50,37.5,and 25 mGy)and three rhesus monkeys(CTDIvol=50 mGy).The collimation width was 128×0.312 5 mm.Images were reconstructed using filtered back projection(FBP),adaptive iterative reconstruction(ClearView,CV30%and CV60%),and deep learning reconstruction(ClearInfinity,CI30%and CI60%).Image quality was evaluated using objective metrics,such as modulation transfer function(MTF),contrast-to-noise ratio(CNR),and artifact severity,as well as double-blind subjective scoring on a 5-point scale.Statistical analyses were then performed.Results:(1)Phantom experiments:At all dose levels,the CNR increased significantly with higher reconstruction levels,with the CI60%images showing a significantly higher CNR than the other algorithms.At 25 mGy,the CNR of CI60%was comparable to that of FBP at 50 mGy,and no significant decrease was observed for MTF10%or MTF50%.(2)Animal experiments:At the centrum semiovale level,the CNR of the CI60%images was significantly higher than that obtained with other algorithms,and artifacts tended to decrease with increasing iteration levels.Inter-observer agreement for image quality assessment was good(Kappa≥0.75).Overall,the subjective scores increased with higher CV/CI levels,with CI60%achieving the highest scores.Conclusion:In UHR detector CT,deep learning reconstruction can improve cranial CT image contrast and reduce noise and artifacts without compromising high-contrast spatial resolution,showing significant potential for radiation dose reduction and demonstrating good clinical application value.

Abstract:Objective:Based on phantom experiments,this study aims to optimize artifacts in multimaterial dentures and provide guidance for clinical practice.Method:A blank control and six denture full-crown models of different materials are placed sequentially at the CIRS phantom center.Subsequently,dual-energy CT scanning is performed using energy CT,and the optimal contrast image of the blank control is reconstructed as a baseline.Next,the optimal contrast images are reconstructed under standard and bone algorithms for the six groups,in addition to virtual monochromatic images at 70-140 keV with an interval of 10 keV.CT and SD values are recorded,and the artifact index(AI)is calculated.Routine scanning is performed and radiation doses of the routine and energy groups are recorded.Two radiologists subjectively evaluate the images of each group and perform a variance analysis or nonparametric tests for data analysis.Results:The radiation dose of the energy group(6.15±0.10)mGy is significantly lower than that of the routine group(30.35±0.02)mGy.The consistency of the subjective image scoring is favorable.As the energy levels increase,the image quality of the energy group improves,whereas the AI decreases.Standard algorithm:The AI values of all modules except the upper fat differ significantly.The AI values of all modules except the upper heavy bone and the light bone differ significantly because of the different denture materials used.Bone algorithm:The AI values of all modules differ significantly,and the AI values of fat and muscle differ significantly owing to the different denture materials.Conclusion:Energy CT significantly reduces the radiation dose.Additionally,pure-titanium dentures have the least number of artifacts and are the preferred material for clinical full crowns.Energy CT combined with virtual single-energy imaging can reduce artifacts and optimize image quality.Recommendations for clinical observation of bone tissue are as follows:Pure titanium,140 keV;cobalt-chromium,90 keV;cobalt-chromium porcelain,140 keV;nickel-chromium,120keV;nickel-chromium porcelain,120 keV;and all ceramic,140 keV.

Abstract:Stroke is the leading cause of disability and mortality among patients with cardiovascular(CV)and cerebrovascular(CBV)diseases in China,with ischemic stroke accounting for approximately 80%of all cases.The core pathological mechanism involves CBV occlusion,whereas capillary obstruction and microcirculatory dysfunction are critical factors that influence disease progression,prognosis,and therapeutic response.Early diagnosis and screening of capillary pathologies during the asymptomatic phase is a fundamental requirement for reducing disease burden.Conventional clinical imaging techniques,such as computed tomography(CT),magnetic resonance imaging(MRI),and digital subtraction angiography(DSA),are effective in diagnosing macrovascular lesions.However,due to limitations in spatial resolution,they are unable to directly visualize cerebral capillaries,which have diameters of 5-10μm.Instead,these techniques indirectly reflect microcirculatory impairments through methods such as CT perfusion to assess the ischemic penumbra or MR diffusion/perfusion imaging to indicate the no-reflow phenomenon.Emerging high-resolution technologies,including optical coherence tomography angiography(OCTA),micro-CT,and two-photon microscopy,enable direct capillary imaging and have demonstrated considerable potential for basic research and retinal microvascular monitoring.However,constraints such as limited penetration depth,invasiveness,and radiation exposure have hindered their clinical translation.This article systematically compared the capabilities of various imaging techniques in detecting cerebral capillaries,aiming to assist clinicians in selecting appropriate microcirculation assessment tools and support researchers in overcoming technological barriers,thereby ultimately advancing the optimization of early diagnostic and screening strategies for ischemic stroke.

Abstract:Computed tomography(CT)technology plays a crucial role in medical diagnosis.Reducing the radiation dose per projection angle while maintaining a constant number of projection angles is an effective approach to achieving low-dose CT.However,this reduction often introduces significant noise into the reconstructed CT images,adversely affecting subsequent image analysis and research.To address this issue,we propose the enhanced restormer for low-dose CT image reconstruction based on multi-attention fusion(ERestormer)for low-dose CT image denoising.The network integrates channel attention,receptive field attention,and multi-head transposed attention to enhance the model's ability to focus on critical information,thereby improving its feature learning capacity.Furthermore,a feature fusion mechanism is introduced to strengthen feature reuse between the encoder and decoder.Experimental results show that the proposed network achieves superior denoising performance and enhanced preservation of image detail when compared to five classical networks:DNCNN,RED-CNN,UNet,Uformer,and Restormer.

Abstract:Objective:To explore the feasibility of using dual low-dose computed tomography(CT)combined with a deep learning image reconstruction(DLIR)algorithm to optimize pulmonary artery mixed reality(MR)imaging.Methods:One-hundred-and-eight patients who planned to undergo pulmonary artery MR imaging at our hospital were prospectively enrolled into this study.They were randomly divided into a low-dose pulmonary artery MR group(Group A:low-dose CT combined with DLIR algorithm,using tube current of 70 kVp and contrast agent of 300 mgI/mL,n=53)and a conventional-dose pulmonary artery MR group(Group B:conventional-dose CT,using tube voltage of 120 kVp and contrast agent of 370 mgI/mL,n=55).In both groups A and B,automatic tube current modulation was applied to the tube currents.Subsequently,the CT DICOM data obtained from the two groups were imported into three-dimensional(3D)visualization modelling software to complete the MR 3D modelling.Demographic characteristics and radiation dose-related indicators of the two patient groups were compared using an independent sample t-test.Additionally,Pearson and Bland-Altman analyses were used to evaluate the consistency of pulmonary artery MR between the two groups,whereas the subjective evaluation of MR quality was conducted using the Mann-Whitney U test.Furthermore,the consistency of the evaluating factors was analyzed using Kappa analysis.Results:Compared to Group B,the radiation dose in Group A decreased by approximately 41%,whereas the quality of the CT DICOM data gradually improved with increasing DLIR intensity.The DICOM images obtained using high-strength DLIR(DLIR-H)demonstrated the best quality.However,there was no significant difference in the quality of the MR between groups A and B.In the Bland-Altman analysis,there was good consistency between groups A and B.Moreover,the subjective consistency of the evaluating factors was good,with a Kappa value of 0.76.Conclusion:The combination of dual low-dose CT and the DLIR algorithm can effectively reduce the radiation and contrast agent doses of pulmonary artery MR without affecting the quality of pulmonary artery MR imaging,laying the foundation for its clinical application and future advancement.

Abstract:The near-source reservoir formation in the Xujiahe Formation of the Sichuan Basin has great exploration potential,but its reservoir types are mostly thin-layered porous and fractured reservoirs with strong vertical and horizontal heterogeneity.The channel sand bodies and small faults are not clearly delineated,requiring high-resolution seismic processing.Moreover,the Xujiahe Formation is more sensitive to low-frequency response;thus,it is necessary to focus on the protection and expansion of low-frequency information while ensuring full-frequency processing.In response to this geological requirement,we have conducted research on near surface Q-compensation technology under low-frequency protection to improve the absorption and attenuation effects near the surface and the impact on the lateral consistency of wavelets,thereby enhancing the quality of seismic data.First,based on the near-surface structural characteristics of the Sichuan Basin and the theory of seismic wave attenuation,the near surface Q-field is established using surface travel time and combined with information such as the dominant frequency of the first seismic arrival.Then,based on the stable Q-compensation method,we propose a new stable Q-compensation process by introducing a low-frequency protection coefficient to protect low frequencies.Finally,the influence of parameters such as the ideal dominant frequency,cutoff frequency,and low-frequency protection coefficient on the compensation effect was compared and analyzed,and the optimal parameter combination for near-surface compensation was established.Based on the optimized parameter combination,the prestack gathers are compensated.The compensation results show that using this process for near surface Q-compensation can effectively improve the resolution of seismic data,restore the amplitude characteristics of sand bodies,and improve the lateral continuity of events.While expanding high frequencies,it can maintain low-frequency information without being suppressed.The attributes extracted from the processed data are consistent with actual drilling results in the work area,significantly improving the accuracy of sand body characterization and providing solid data and technical support for subsequent oil and gas exploration.

Abstract:In photon-counting computerized tomography(PCCT),the detector can only receive partial photon energy within a single energy channel,resulting in limited photon counting rates and a significantly reduced signal-to-noise ratio of the projection data.Aiming at the limitation that strongly supervised denoising methods rely on large-scale paired datasets and to address the issue that weakly supervised methods using unpaired data have insufficient denoising performance,this study proposes a weakly supervised projection denoising method based on an optimal transport network.The method first adaptively matches the noise and reference distributions by constructing an optimal transport constraint term for projection data consistency.Second,an optimal transport generative adversarial network framework integrated with attention mechanisms was designed to synchronously optimize noise suppression and detail recovery capabilities under unpaired training conditions.Finally,the framework was used to process noisy projections and perform image reconstruction,verifying the feature consistency transfer from the projection to the image domain.In experiments,compared with mainstream denoising methods,the proposed method achieved a peak signal-to-noise ratio improvement of 0.47 dB and increased the structural similarity from 0.75 to 0.81 on the PCCT projection dataset.This study provides a robust denoising solution for PCCT imaging that does not require precisely paired datasets.

Abstract:Objective:To compare image quality between deep learning image reconstruction(DLIR)low-dose chest CT and iterative reconstruction(ASIR-V)standard-dose chest CT in patients with chronic obstructive pulmonary disease(COPD).Methods:A total of 106 patients were prospectively enrolled and underwent standard-dose(SD)and low-dose(LD)chest CT scans.The LD scans were reconstructed using ASIR-V(LD-AR)and three DLIR strength levels(LD-DL/DM/DH),whereas the SD scans were reconstructed using ASIR-V(SD-AR).Noise(standard deviation),signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR)of the anatomical structures were measured or calculated.The subjective image quality was scored by radiologists.Results:Effective radiation dose was(4.0±1.37)mSv for the SD group and(1.14±0.47)mSv for the LD group.The LD-DLIR images exhibited lower noise,higher SNR,and higher CNR than the SD-AR images,with the LD-DH performing the best.Subjective scores indicated superior noise levels,anatomical clarity,and emphysema visualization in LD-DLIR images compared to SD-AR,with LD-DH receiving the highest score.Conclusion:DLIR significantly improved chest CT image quality in patients with COPD while reducing the radiation dose by 71.5%,with DLIR-H providing optimal performance.