Triple-path feature transform network for ring-array photoacoustic tomography image reconstruction

Photoacoustic imaging(PAI)is a noninvasive emerging imaging method based on the photoacoustic effect,which provides necessary assistance for medical diagnosis.It has the characteristics of large imaging depth and high contrast.However,limited by the equipment cost and reconstruction time requirements,the existing PAI systems distributed with annular array transducers are difficult to take into account both the image quality and the imaging speed.In this paper,a triple-path feature transform network(TFT-Net)for ring-array photoacoustic tomography is proposed to enhance the imaging quality from limited-view and sparse measurement data.Specifically,the network combines the raw photoacoustic pressure signals and conventional linear reconstruction images as input data,and takes the photoacoustic physical model as a prior information to guide the reconstruction process.In addition,to enhance the ability of extracting signal features,the residual block and squeeze and excitation block are introduced into the TFT-Net.For further efficient reconstruction,the final output of photoacoustic signals uses‘filter-then-upsample’operation with a pixel-shuffle multiplexer and a max out module.Experiment results on simulated and in-vivo data demonstrate that the constructed TFT-Net can restore the target boundary clearly,reduce background noise,and realize fast and high-quality photoacoustic image reconstruction of limited view with sparse sampling.

Deep learning-based inpainting of saturation artifacts in optical coherence tomography images

Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.

Intravascular photoacoustic and optical coherence tomography imaging dual-mode system for detecting spontaneous coronary artery dissection: A feasibility study

In this work,we present an intravascular dual-mode endoscopic system capable of both intravascular photoacoustic imaging(IVPAI)and intravascular optical coherence tomography(IVOCT)for recognizing spontaneous coronary artery dissection(SCAD)phantoms.IVPAI provides high-resolution and high-penetration images of intramural hematoma(IMH)at different depths,so it is especially useful for imaging deep blood clots associated with imaging phantoms.IVOCT can readily visualize the double-lumen morphology of blood vessel walls to identify intimal tears.We also demonstrate the capability of this dual-mode endoscopic system using mimicking phantoms and biological samples of blood clots in ex vivo porcine arteries.The results of the experiments indicate that the combined IVPAI and IVOCT technique has the potential to provide a more accurate SCAD assessment method for clinical applications.

Multidetector computer tomography and magnetic resonance imaging of double superior mesenteric veins:A case report

BACKGROUND This study aimed to describe the findings of double superior mesenteric veins(SMVs),a rare anatomical variation,on multidetector computer tomography(MDCT)and magnetic resonance imaging(MRI)images.CASE SUMMARY We describe the case of a 34-year-old male,who underwent both MDC and MRI examinations of the upper abdomen because of liver cirrhosis.MDCT and MRI angiography images of the upper abdomen revealed an anatomic variation of the superior mesenteric vein(SMV),the double SMVs.CONCLUSION The double SMVs are a congenital abnormality without potential clinical manifestation.Physicians need to be aware of this anatomical variation during abdominal surgery to avoid iatrogenic injury.

Artificial Intelligence-Based Image Reconstruction for Computed Tomography: A Survey

Computed tomography has made significant advances since its intro-duction in the early 1970s,where researchers have mainly focused on the quality of image reconstruction in the early stage.However,radiation exposure poses a health risk,prompting the demand of the lowest possible dose when carrying out CT examinations.To acquire high-quality reconstruction images with low dose radiation,CT reconstruction techniques have evolved from conventional reconstruction such as analytical and iterative reconstruction,to reconstruction methods based on artificial intelligence(AI).All these efforts are devoted to con-structing high-quality images using only low doses with fast reconstruction speed.In particular,conventional reconstruction methods usually optimize one aspect,while AI-based reconstruction has finally managed to attain all goals in one shot.However,there are limitations such as the requirements on large datasets,unstable performance,and weak generalizability in AI-based reconstruction methods.This work presents the review and discussion on the classification,the commercial use,the advantages,and the limitations of AI-based image reconstruction methods in CT.

Tomographic reconstruction of the Earth’s magnetosheath from multiple spacecraft:a theoretical study

Following our earlier work on tomographic reconstruction of the magnetosheath soft X-ray emissions with superposed epoch analysis of many images recorded from a single spacecraft we now explore the instantaneous reconstruction of the magnetosheath and magnetopause using a few images recorded simultaneously from a few spacecraft.This work is motivated by the prospect of possibly having two or three soft X-ray imagers in space in the coming years,and that many phenomena which occur at the magnetopause boundary,such as reconnection events and pressure pulse responses,do not lend themselves as well to superposed epoch analysis.If the reconstruction is successful-which we demonstrate in this paper that it can be-this collection of imagers can be used to reconstruct the magnetosheath and magnetopause from a single image from each spacecraft,allowing for high time resolution reconstructions.In this paper we explore the reconstruction using,two,three,and four spacecraft.We show that the location of the subsolar point of the magnetopause can be determined with just two satellites,and that volume emissions of soft X-rays,and the shape of the boundary,can be reconstructed using three or more satellites.

The risk of prostate cancer on incidental finding of an avid prostate uptake on 2-deoxy-2-[^(18)F]fluoro-D-glucose positron emission tomography/computed tomography for non-prostate cancer-related pathology:A single centre retrospective study

Objective:To review the risk of prostate cancer(PCa)in men with incidentally reported increased intraprostatic uptake at 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography/computed tomography(18F-FDG PET/CT)ordered at Department of Urology,The Wesley Hospital,Brisbane,QLD,Australia for non-PCa related pathology.Methods:Retrospective analysis of consecutive men between August 2014 and August 2019 presenting to a single institution for 18F-FDG PET/CT for non-prostate related conditions was conducted.Men were classified as benign,indeterminate,or malignant depending of the results of prostate-specific antigen(PSA),PSA velocity,biopsy histopathology,and three-Tesla(3 T)multiparametric MRI(mpMRI)Prostate Imaging Reporting and Data System score,or gallium-68-prostate-specific membrane antigen(68Ga-PSMA)PET/CT results.Results:Three percent(273/9122)of men demonstrated 18F-FDG avidity within the prostate.Eighty-five percent(231/273)were further investigated,including with PSA tests(227/231,98.3%),3 T mpMRI(68/231,29.4%),68Ga-PSMA PET/CT(33/231,14.3%),and prostate biopsy(57/231,24.7%).Results were considered benign in 130/231(56.3%),indeterminate in 31/231(13.4%),and malignant in 70/231(30.3%).PCa was identified in 51/57(89.5%)of the men who proceeded to biopsy,including 26/27(96.3%)men with Prostate Imaging Reporting and Data System scores 4-5 mpMRI and six men with a positive 68Ga-PSMA PET/CT.The most common Gleason score on biopsy was greater than or equal to 4+5(14/51,27.5%).68Ga-PSMA PET/CT was concordant with the 18F-FDG findings in 26/33(78.8%).All 13 men with a positive concordant 18F-FDG,3 T mpMRI,and 68Ga-PSMA PET/CT had PCa on biopsy.There was no statistically significant difference in the 18F-FDG maximum standardized uptake value between the benign or malignant groups(5.7 vs.6.1;p=0.580).Conclusion:In this study,after an incidental finding of an avid intraprostatic lesion on 18F-FDG PET/CT,70 of the 231 cases(30.3%;0.8%of the entire cohort)had results consistent with PCa,most commonly as Gleason score greater than or equal to 4+5 disease.Unless there is limited life expectancy due to competing medical co-morbidity,men with an incidental finding of intraprostatic uptake on 18F-FDG should be further investigated using principles of PCa detection.

Multimodal imaging in the diagnosis of bone giant cell tumors:A retrospective study

BACKGROUND Giant cell tumor of bone is a locally aggressive and rarely metastasizing tumor,and also a potential malignant tumor that may develop into a primary malignant giant cell tumor.AIM To evaluate the role of multimodal imaging in the diagnosis of giant cell tumors of bone.METHODS The data of 32 patients with giant cell tumor of bone confirmed by core-needle biopsy or surgical pathology at our hospital between March 2018 and March 2023 were retrospectively selected.All the patients with giant cell tumors of the bone were examined by X-ray,computed tomography(CT)and magnetic resonance imaging(MRI),and 7 of them were examined by positron emission tomography(PET)-CT.RESULTS X-ray imaging can provide overall information on giant cell tumor lesions.CT and MRI can reveal the characteristics of the internal structure of the tumor as well as the adjacent relationships of the tumor,and these methods have unique advantages for diagnosing tumors and determining the scope of surgery.PET-CT can detect small lesions and is highly valuable for identifying benign and malignant tumors to aid in the early diagnosis of metastasis.CONCLUSION Multimodal imaging plays an important role in the diagnosis of giant cell tumor of bone and can provide a reference for the treatment of giant cell tumors.

Detecting early changes in choroidal vascularity and thickness using optical coherence tomography in patients with corneal crosslinking for keratoconus

AIM:To investigate changes in choroidal thickness and vascularity in keratoconus patients treated with corneal crosslinking.METHODS:This study evaluated 28 eyes of 22 patients with keratoconus who underwent corneal crosslinking.The choroidal thicknesses were evaluated on enhanced depth imaging optical coherence tomography at the preoperative and postoperative 3d,1,and 3mo.Choroidal thickness in the four cardinal quadrants and the fovea were evaluated.The choroidal vascularity index was also calculated.RESULTS:There was no significant difference in central choroidal thickness between the preoperative and postoperative 3d,1mo(P>0.05).There was a significant increase in the 3mo(P=0.034)and a significant decrease in the horizontal choroidal vascularity index on the postoperative 3d(P=0.014),there was no statistically significant change in vertical axes and other visits in horizontal sections(P>0.05).CONCLUSION:This study sheds light on choroidal changes in postoperative corneal crosslinking for keratoconus.While it suggests the procedure’s relative safety for submacular choroid,more extensive research is necessary to confirm these findings and their clinical significance.

Insights into the hydrogen evolution reaction in vanadium redox flow batteries:A synchrotron radiation based X-ray imaging study

The parasitic hydrogen evolution reaction(HER)in the negative half-cell of vanadium redox flow batteries(VRFBs)causes severe efficiency losses.Thus,a deeper understanding of this process and the accompanying bubble formation is crucial.This benchmarking study locally analyzes the bubble distribution in thick,porous electrodes for the first time using deep learning-based image segmentation of synchrotron X-ray micro-tomograms.Each large three-dimensional data set was processed precisely in less than one minute while minimizing human errors and pointing out areas of increased HER activity in VRFBs.The study systematically varies the electrode potential and material,concluding that more negative electrode potentials of-200 m V vs.reversible hydrogen electrode(RHE)and lower cause more substantial bubble formation,resulting in bubble fractions of around 15%–20%in carbon felt electrodes.Contrarily,the bubble fractions stay only around 2%in an electrode combining carbon felt and carbon paper.The detected areas with high HER activity,such as the border subregion with more than 30%bubble fraction in carbon felt electrodes,the cutting edges,and preferential spots in the electrode bulk,are potential-independent and suggest that larger electrodes with a higher bulk-to-border ratio might reduce HER-related performance losses.The described combination of electrochemical measurements,local X-ray microtomography,AI-based segmentation,and 3D morphometric analysis is a powerful and novel approach for local bubble analysis in three-dimensional porous electrodes,providing an essential toolkit for a broad community working on bubble-generating electrochemical systems.

Transparent and Accurate COVID-19 Diagnosis:Integrating Explainable AI with Advanced Deep Learning in CT Imaging

In the current landscape of the COVID-19 pandemic,the utilization of deep learning in medical imaging,especially in chest computed tomography(CT)scan analysis for virus detection,has become increasingly significant.Despite its potential,deep learning’s“black box”nature has been a major impediment to its broader acceptance in clinical environments,where transparency in decision-making is imperative.To bridge this gap,our research integrates Explainable AI(XAI)techniques,specifically the Local Interpretable Model-Agnostic Explanations(LIME)method,with advanced deep learning models.This integration forms a sophisticated and transparent framework for COVID-19 identification,enhancing the capability of standard Convolutional Neural Network(CNN)models through transfer learning and data augmentation.Our approach leverages the refined DenseNet201 architecture for superior feature extraction and employs data augmentation strategies to foster robust model generalization.The pivotal element of our methodology is the use of LIME,which demystifies the AI decision-making process,providing clinicians with clear,interpretable insights into the AI’s reasoning.This unique combination of an optimized Deep Neural Network(DNN)with LIME not only elevates the precision in detecting COVID-19 cases but also equips healthcare professionals with a deeper understanding of the diagnostic process.Our method,validated on the SARS-COV-2 CT-Scan dataset,demonstrates exceptional diagnostic accuracy,with performance metrics that reinforce its potential for seamless integration into modern healthcare systems.This innovative approach marks a significant advancement in creating explainable and trustworthy AI tools for medical decisionmaking in the ongoing battle against COVID-19.

Biliary complications after liver transplantation:A computed tomography and magnetic resonance imaging pictorial review

Biliary complications are the most common complications after liver transplantation.Computed tomography(CT)and magnetic resonance imaging(MRI)are cornerstones for timely diagnosis of biliary complications after liver transplantation.The diagnosis of these complications by CT and MRI requires expertise,mainly with respect to identifying subtle early signs to avoid missed or incorrect diagnoses.For example,biliary strictures may be misdiagnosed on MRI due to size mismatch of the common ducts of the donor and recipient,postoperative edema,pneumobilia,or susceptibility artifacts caused by surgical clips.Proper and prompt diagnosis of biliary complications after transplantation allows the timely initiation of appropriate management.The aim of this pictorial review is to illustrate various CT and MRI findings related to biliary complications after liver transplantation,based on time of presentation after surgery and frequency of occurrence.

Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

Chronic pancreatitis:Pain and computed tomography/magnetic resonance imaging findings

Chronic pancreatitis(CP)is a fibroinflammatory disease characterized by irreversible destruction of pancreatic tissue.With the development of the disease,it may lead to exocrine and/or endocrine insufficiency.CP is one of the common diseases that cause abdominal pain,which will not get permanent spontaneous relief as the disease evolves.The American College of Gastroenterology clinical guidelines recommend computed tomography or magnetic resonance imaging as the first-line examination for the diagnosis of CP.CP common imaging findings include pancreatic atrophy,irregular dilatation of the pancreatic duct,calcification of pancreatic parenchyma,pancreatic duct stones,etc.In clinical practice,whether any correlations between CP-induced abdominal pain patterns(no pain/constant/intermittent pain)and corresponding imaging findings present are not well known.Therefore,this review aims to comprehensively sort out and analyze the relevant information by collecting lots of literature on this field,so as to construct a cross-bridge between the clinical manifestations and imaging manifestations of CP patients.Also,it provides an imaging basis and foundation for the classification and diagnosis of abdominal pain types in clinical CP patients.

Extravasated contrast volumetric assessment on computed tomography angiography in gastrointestinal bleeding:A useful predictor of positive angiographic findings

BACKGROUND Gastrointestinal bleeding(GIB)is a severe and potentially life-threatening condition,especially in cases of delayed treatment.Computed tomography angiography(CTA)plays a pivotal role in the early identification of upper and lower GIB and in the prompt treatment of the haemorrhage.AIM To determine whether a volumetric estimation of the extravasated contrast at CTA in GIB may be a predictor of subsequent positive angiographic findings.METHODS In this retrospective single-centre study,35 patients(22 men;median age 69 years;range 16-92 years)admitted to our institution for active GIB detected at CTA and further submitted to catheter angiography between January 2018 and February 2022 were enrolled.Twenty-three(65.7%)patients underwent endoscopy before CTA.Bleeding volumetry was evaluated in both arterial and venous phases via a semi-automated dedicated software.Bleeding rate was obtained from volume change between the two phases and standardised for unit time.Patients were divided into two groups,according to the angiographic signs and their concordance with CTA.RESULTS Upper bleeding accounted for 42.9%and lower GIB for 57.1%.Mean haemoglobin value at the admission was 7.7 g/dL.A concordance between positive CTA and direct angiographic bleeding signs was found in 19(54.3%)cases.Despite no significant differences in terms of bleeding volume in the arterial phase(0.55 mL vs 0.33 mL,P=0.35),a statistically significant volume increase in the venous phase was identified in the group of patients with positive angiography(2.06 mL vs 0.9 mL,P=0.02).In the latter patient group,a significant increase in bleeding rate was also detected(2.18 mL/min vs 0.19 mL/min,P=0.02).CONCLUSION In GIB of any origin,extravasated contrast volumetric analysis at CTA could be a predictor of positive angiography and may help in avoiding further unnecessary procedures.

Cardiac CT Image Segmentation for Deep Learning-Based Coronary Calcium Detection Using K-Means Clustering and Grabcut Algorithm

Specific medical data has limitations in that there are not many numbers and it is not standardized.to solve these limitations,it is necessary to study how to efficiently process these limited amounts of data.In this paper,deep learning methods for automatically determining cardiovascular diseases are described,and an effective preprocessing method for CT images that can be applied to improve the performance of deep learning was conducted.The cardiac CT images include several parts of the body such as the heart,lungs,spine,and ribs.The preprocessing step proposed in this paper divided CT image data into regions of interest and other regions using K-means clustering and the Grabcut algorithm.We compared the deep learning performance results of original data,data using only K-means clustering,and data using both K-means clustering and the Grabcut algorithm.All data used in this paper were collected at Soonchunhyang University Cheonan Hospital in Korea and the experimental test proceeded with IRB approval.The training was conducted using Resnet 50,VGG,and Inception resnet V2 models,and Resnet 50 had the best accuracy in validation and testing.Through the preprocessing process proposed in this paper,the accuracy of deep learning models was significantly improved by at least 10%and up to 40%.

Analysis of Imaging Characteristics and Dynamic Changes of 3 Cases of Severe Novel Coronavirus Pneumonia in Qinghai Province

Objective:To analyze the characteristics,dynamic changes,and outcomes of the first imaging manifestations of 3 patients with severe COVID-19 in our hospital.Methods:Computed tomography(CT)findings of 3 patients with severe COVID-19 who tested positive by the nucleic acid test in our hospital were selected,mainly focusing on the morphology,distribution characteristics,and dynamic changes of the first CT findings.Results:3 patients with severe pneumonia were older,with one aged 80.The first chest CT examination for all 3 patients differed.Imaging showed a leafy distribution of consolidation,primarily affecting the lower lobes of both lungs and extending subpleurally.A grid-like pattern was observed,along with changes in the consolidation and air bronchogram.These changes had slower absorption,especially in patients with underlying diseases.Conclusion:CT manifestations of severe COVID-19 have specific characteristics and the analysis of their characteristics and dynamic changes provide valuable insights for clinical treatment.

Analysis of The Value of Multi-Slice Spiral CT and Magnetic Resonance Imaging in The Diagnosis of Carpal Joint Injury

Objective:To analyze the value of multi-slice spiral computed tomography(CT)and magnetic resonance imaging(MRI)in the diagnosis of carpal joint injury.Methods:A total of 130 patients with suspected wrist injuries admitted to the Department of Orthopedics of our hospital from January 2023 to January 2024 were selected and randomly divided into a single group(n=65)and a joint group(n=65).The single group was diagnosed using multi-slice spiral CT,and the joint group was diagnosed using multi-slice spiral CT and magnetic resonance imaging,with pathological diagnosis as the gold standard.The diagnostic results of both groups were compared to the gold standard,and the diagnostic energy efficiency of both groups was compared.Results:The diagnostic results of the single group compared with the gold standard were significant(P<0.05).The diagnostic results of the joint group compared with the gold standard were not significant(P>0.05).The sensitivity and accuracy of diagnosis in the joint group were significantly higher than that in the single group(P<0.05).The specificity of diagnosis in the joint group was higher as compared to that in the single group(P>0.05).Conclusion:The combination of multi-slice spiral CT and MRI was highly accurate in diagnosing wrist injuries,and the misdiagnosis rate and leakage rate were relatively low.Hence,this diagnostic program is recommended to be popularized.

Surgical complications after pancreatic transplantation:A computed tomography imaging pictorial review

Pancreatic transplantation is considered by the American Diabetes Association and the European Association for the Study of Diabetes an acceptable surgical procedure in patients with type 1 diabetes also undergoing kidney transplantation in pre-final or end-stage renal disease if no contraindications are present.Pancreatic transplantation,however,is a complex surgical procedure and may lead to a range of postoperative complications that can significantly impact graft function and patient outcomes.Postoperative computed tomography(CT)is often adopted to evaluate perfusion of the transplanted pancreas,identify complications and as a guide for interventional radiology procedures.CT assessment after pancreatic transplantation should start with the evaluation of the arterial Y-graft,the venous anastomosis and the duodenojejunostomy.With regard to complications,CT allows for the identification of vascular complications,such as thrombosis or stenosis of blood vessels supplying the graft,the detection of pancreatic fluid collections,including pseudocysts,abscesses,or leaks,the assessment of bowel complications(anastomotic leaks,ileus or obstruction),and the identification of bleeding.The aim of this pictorial review is to illustrate CT findings of surgical-related complications after pancreatic transplantation.The knowledge of surgical techniques is of key importance to understand postoperative anatomic changes and imaging evaluation.Therefore,we first provide a short summary of the main techniques of pancreatic transplantation.Then,we provide a practical imaging approach to pancreatic transplantation and its complications providing tips and tricks for the prompt imaging diagnosis on CT.

A new imaging mode based on X-ray CT as prior image and sparsely sampled projections for rapid clinical proton CT

Proton computed tomography(CT)has a distinct practical significance in clinical applications.It eliminates 3–5%errors caused by the transformation of Hounsfield unit(HU)to relative stopping power(RSP)values when using X-ray CT for positioning and treatment planning systems(TPSs).Following the development of FLASH proton therapy,there are increased requirements for accurate and rapid positioning in TPSs.Thus,a new rapid proton CT imaging mode is proposed based on sparsely sampled projections.The proton beam was boosted to 350 MeV by a compact proton linear accelerator(LINAC).In this study,the comparisons of the proton scattering with the energy of 350 MeV and 230 MeV are conducted based on GEANT4 simulations.As the sparsely sampled information associated with beam acquisitions at 12 angles is not enough for reconstruction,X-ray CT is used as a prior image.The RSP map generated by converting the X-ray CT was constructed based on Monte Carlo simulations.Considering the estimation of the most likely path(MLP),the prior image-constrained compressed sensing(PICCS)algorithm is used to reconstruct images from two different phantoms using sparse proton projections of 350 MeV parallel proton beam.The results show that it is feasible to realize the proton image reconstruction with the rapid proton CT imaging proposed in this paper.It can produce RSP maps with much higher accuracy for TPSs and fast positioning to achieve ultra-fast imaging for real-time image-guided radiotherapy(IGRT)in clinical proton therapy applications.