An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

Experimental and numerical study of hypervelocity impact damage on composite overwrapped pressure vessels

Ground-based tests are important for studying hypervelocity impact(HVI)damage to spacecraft pressure vessels in the orbital debris environment.We analyzed the damage to composite overwrapped pressure vessels(COPVs)in the HVI tests and classified the damage into non-catastrophic damage and catastrophic damage.We proposed a numerical simulation method to further study non-catastrophic damage and revealed the characteristics and mechanisms of non-catastrophic damage affected by impact conditions and internal pressures.The fragments of the catastrophically damaged COPVs were collected after the tests.The crack distribution and propagation process of the catastrophic ruptures of the COPVs were analyzed.Our findings contribute to understanding the damage characteristics and mechanisms of COPVs by HVIs.

A Deformable Network with Attention Mechanism for Retinal Vessel Segmentation

The intensive application of deep learning in medical image processing has facilitated the advancement of automatic retinal vessel segmentation research.To overcome the limitation that traditional U-shaped vessel segmentation networks fail to extract features in fundus image sufficiently,we propose a novel network(DSeU-net)based on deformable convolution and squeeze excitation residual module.The deformable convolution is utilized to dynamically adjust the receptive field for the feature extraction of retinal vessel.And the squeeze excitation residual module is used to scale the weights of the low-level features so that the network learns the complex relationships of the different feature layers efficiently.We validate the DSeU-net on three public retinal vessel segmentation datasets including DRIVE,CHASEDB1,and STARE,and the experimental results demonstrate the satisfactory segmentation performance of the network.

Meningeal lymphatic vessel crosstalk with central nervous system immune cells in aging and neurodegenerative diseases

Meningeal lymphatic vessels form a relationship between the nervous system and periphery, which is relevant in both health and disease. Meningeal lymphatic vessels not only play a key role in the drainage of brain metabolites but also contribute to antigen delivery and immune cell activation. The advent of novel genomic technologies has enabled rapid progress in the characterization of myeloid and lymphoid cells and their interactions with meningeal lymphatic vessels within the central nervous system. In this review, we provide an overview of the multifaceted roles of meningeal lymphatic vessels within the context of the central nervous system immune network, highlighting recent discoveries on the immunological niche provided by meningeal lymphatic vessels. Furthermore, we delve into the mechanisms of crosstalk between meningeal lymphatic vessels and immune cells in the central nervous system under both homeostatic conditions and neurodegenerative diseases, discussing how these interactions shape the pathological outcomes. Regulation of meningeal lymphatic vessel function and structure can influence lymphatic drainage, cerebrospinal fluid-borne immune modulators, and immune cell populations in aging and neurodegenerative disorders, thereby playing a key role in shaping meningeal and brain parenchyma immunity.

Repeatability,interocular correlation and agreement of optic nerve head vessel density in healthy eyes:a sweptsource optical coherence tomographic angiography study

AIM:To assess the repeatability,interocular correlation,and agreement of quantitative swept-source optical coherence tomography angiography(OCTA)optic nerve head(ONH)parameters in healthy subjects.METHODS:Thir ty-three healthy subjects were enrolled.The ONH of both eyes were imaged four times by a swept-source-OCTA using a 3 mm×3 mm scanning protocol.Images of the radial peripapillary capillary were analyzed by a customized Matlab program,and the vessel density,fractal dimension,and vessel diameter index were measured.The repeatability of the four scans was determined by the intraclass correlation coefficient(ICC).The most well-centered optic disc from the four repeated scans was then selected for the interocular correlation and agreement analysis using the Pearson correlation coefficient,ICC and Bland-Altman plots.RESULTS:All swept-source-OCTA ONH parameters exhibited certain repeatability,with ICC>0.760 and coefficient of variation(CoV)≤7.301%.The obvious interocular correlation was observed for papillary vessel density(ICC=0.857),vessel diameter index(ICC=0.857)and fractal dimension(ICC=0.906),while circumpapillary vessel density exhibited moderate interocular correlation(ICC=0.687).Bland-Altman plots revealed an agreement range of-5.26%to 6.21%for circumpapillary vessel density.CONCLUSION:OCTA ONH parameters demonstrate good repeatability in healthy subjects.The interocular correlations of papillary vessel density,fractal dimension and vessel diameter index are high,but the correlation for circumpapillary vessel density is moderate.

Clinical Value of the Quantitative Flow Ratio to Predict Long-term Target Vessel Failure in Patients with In-stent Restenosis after Drug-coated Balloon Angioplasty

Objective The study sought to investigate the clinical predictive value of quantitative flow ratio(QFR)for the long-term target vessel failure(TVF)outcome in patients with in-stent restenosis(ISR)by using drug-coated balloon(DCB)treatment after a long-term follow-up.Methods This was a retrospective study.A total of 186 patients who underwent DCB angioplasty for ISR in two hospitals from March 2014 to September 2019 were enrolled.The QFR of the entire target vessel was measured offline.The primary endpoint was TVF,including target vessel-cardiac death(TV-CD),target vessel-myocardial infarction(TV-MI),and clinically driven-target vessel revascularization(CD-TVR).Results The follow-up time was 3.09±1.53 years,and 50 patients had TVF.The QFR immediately after percutaneous coronary intervention(PCI)was significantly lower in the TVF group than in the no-TVF group.Multivariable Cox regression analysis indicated that the QFR immediately after PCI was an excellent predictor for TVF after the long-term follow-up[hazard ratio(HR):5.15×10−5(6.13×10−8−0.043);P<0.01].Receiver-operating characteristic(ROC)curve analysis demonstrated that the optimal cut-off value of the QFR immediately after PCI for predicting the long-term TVF was 0.925(area under the curve:0.886,95%confidence interval:0.834–0.938;sensitivity:83.40%,specificity:88.00;P<0.01).In addition,QFR≤0.925 post-PCI was strongly correlated with the TVF,including TV-MI and CD-TVR(P<0.01).Conclusion The QFR immediately after PCI showed a high predictive value of TVF after a long-term follow-up in ISR patients who underwent DCB angioplasty.A lower QFR immediately after PCI was associated with a worse TVF outcome.

Predictive visual field outcomes after optic chiasm decompressive surgery by retinal vessels parameters using optical coherence tomography angiography

AIM:To evaluate the predictive value of superficial retinal capillary plexus(SRCP)and radial peripapillary capillary(RPC)for visual field recovery after optic cross decompression and compare them with peripapillary nerve fiber layer(pRNFL)and ganglion cell complex(GCC).METHODS:This prospective longitudinal observational study included patients with chiasmal compression due to sellar region mass scheduled for decompressive surgery.Generalized estimating equations were used to compare retinal vessel density and retinal layer thickness preand post-operatively and with healthy controls.Logistic regression models were used to assess the relationship between preoperative GCC,pRNFL,SRCP,and RPC parameters and visual field recovery after surgery.RESULTS:The study included 43 eyes of 24 patients and 48 eyes of 24 healthy controls.Preoperative RPC and SRCP vessel density and pRNFL and GCC thickness were lower than healthy controls and higher than postoperative values.The best predictive GCC and pRNFL models were based on the superior GCC[area under the curve(AUC)=0.866]and the tempo-inferior pRNFL(AUC=0.824),and the best predictive SRCP and RPC models were based on the nasal SRCP(AUC=0.718)and tempo-inferior RPC(AUC=0.825).There was no statistical difference in the predictive value of the superior GCC,tempo-inferior pRNFL,and tempo-inferior RPC(all P>0.05).CONCLUSION:Compression of the optic chiasm by tumors in the saddle area can reduce retinal thickness and blood perfusion.This reduction persists despite the recovery of the visual field after decompression surgery.GCC,pRNFL,and RPC can be used as sensitive predictors of visual field recovery after decompression surgery.

Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma:Machine learning model based on contrast-enhanced computed tomography

BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner,and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma(HCC).AIM To develop and validate a preoperative nomogram using contrast-enhanced computed tomography(CECT)to predict the presence of VETC+in HCC.METHODS We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers.Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase.Radiomics features,essential for identifying VETC+HCC,were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set.The model’s performance was validated on two separate test sets.Receiver operating characteristic(ROC)analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets.The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features.ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features,the radiomics features and the radiomics nomogram.RESULTS The study included 190 individuals from two independent centers,with the majority being male(81%)and a median age of 57 years(interquartile range:51-66).The area under the curve(AUC)for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825,0.788,and 0.680 in the training set and the two test sets.A total of 13 features were selected to construct the Rad-score.The nomogram,combining clinicalradiological and combined radiomics features could accurately predict VETC+in all three sets,with AUC values of 0.859,0.848 and 0.757.Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models.CONCLUSION This study demonstrates the potential utility of a CECT-based radiomics nomogram,incorporating clinicalradiological features and combined radiomics features,in the identification of VETC+HCC.

Investigating the relationship between intracranial atherosclerotic plaque remodelling and diabetes using high-resolution vessel wall imaging

BACKGROUND Intracranial atherosclerosis,a leading cause of stroke,involves arterial plaque formation.This study explores the link between plaque remodelling patterns and diabetes using high-resolution vessel wall imaging(HR-VWI).AIM To investigate the factors of intracranial atherosclerotic remodelling patterns and the relationship between intracranial atherosclerotic remodelling and diabetes mellitus using HR-VWI.METHODS Ninety-four patients diagnosed with middle cerebral artery or basilar artery INTRODUCTION Intracranial atherosclerotic disease is one of the main causes of ischaemic stroke in the world,accounting for approx-imately 10%of transient ischaemic attacks and 30%-50%of ischaemic strokes[1].It is the most common factor among Asian people[2].The adaptive changes in the structure and function of blood vessels that can adapt to changes in the internal and external environment are called vascular remodelling,which is a common and important pathological mechanism in atherosclerotic diseases,and the remodelling mode of atherosclerotic plaques is closely related to the occurrence of stroke.Positive remodelling(PR)is an outwards compensatory remodelling where the arterial wall grows outwards in an attempt to maintain a constant lumen diameter.For a long time,it was believed that the degree of stenosis can accurately reflect the risk of ischaemic stroke[3-5].Previous studies have revealed that lesions without significant luminal stenosis can also lead to acute events[6,7],as summarized in a recent meta-analysis study in which approximately 50%of acute/subacute ischaemic events were due to this type of lesion[6].Research[8,9]has pointed out that the PR of plaques is more dangerous and more likely to cause acute ischaemic stroke.Previous studies[10-13]have found that there are specific vascular remodelling phenomena in the coronary and carotid arteries of diabetic patients.However,due to the deep location and small lumen of intracranial arteries and limitations of imaging techniques,the relationship between intracranial arterial remodelling and diabetes is still unclear.In recent years,with the development of magnetic resonance technology and the emergence of high-resolution(HR)vascular wall imaging,a clear and multidimensional display of the intracranial vascular wall has been achieved.Therefore,in this study,HR wall imaging(HR-VWI)was used to display the remodelling characteristics of bilateral middle cerebral arteries and basilar arteries and to explore the factors of intracranial vascular remodelling and its relationship with diabetes.

Nomogram prediction of vessels encapsulating tumor clusters in small hepatocellular carcinoma≤3 cm based on enhanced magnetic resonance imaging

BACKGROUND Vessels encapsulating tumor clusters(VETC)represent a recently discovered vascular pattern associated with novel metastasis mechanisms in hepatocellular carcinoma(HCC).However,it seems that no one have focused on predicting VETC status in small HCC(sHCC).This study aimed to develop a new nomogram for predicting VETC positivity using preoperative clinical data and image features in sHCC(≤3 cm)patients.AIM To construct a nomogram that combines preoperative clinical parameters and image features to predict patterns of VETC and evaluate the prognosis of sHCC patients.METHODS A total of 309 patients with sHCC,who underwent segmental resection and had their VETC status confirmed,were included in the study.These patients were recruited from three different hospitals:Hospital 1 contributed 177 patients for the training set,Hospital 2 provided 78 patients for the test set,and Hospital 3 provided 54 patients for the validation set.Independent predictors of VETC were identified through univariate and multivariate logistic analyses.These independent predictors were then used to construct a VETC prediction model for sHCC.The model’s performance was evaluated using the area under the curve(AUC),calibration curve,and clinical decision curve.Additionally,Kaplan-Meier survival analysis was performed to confirm whether the predicted VETC status by the model is associated with early recurrence,just as it is with the actual VETC status and early recurrence.RESULTS Alpha-fetoprotein_lg10,carbohydrate antigen 199,irregular shape,non-smooth margin,and arterial peritumoral enhancement were identified as independent predictors of VETC.The model incorporating these predictors demonstrated strong predictive performance.The AUC was 0.811 for the training set,0.800 for the test set,and 0.791 for the validation set.The calibration curve indicated that the predicted probability was consistent with the actual VETC status in all three sets.Furthermore,the decision curve analysis demonstrated the clinical benefits of our model for patients with sHCC.Finally,early recurrence was more likely to occur in the VETC-positive group compared to the VETC-negative group,regardless of whether considering the actual or predicted VETC status.CONCLUSION Our novel prediction model demonstrates strong performance in predicting VETC positivity in sHCC(≤3 cm)patients,and it holds potential for predicting early recurrence.This model equips clinicians with valuable information to make informed clinical treatment decisions.

Quantifying peripapillary vessel density and retinal nerve fibre layer in type 1 diabetic children without clinically detectable retinopathy using OCTA

AIM:To quantify changes in radial peripapillary capillary vessel density(ppVD)and the peripapillary retinal nerve fiber layer(pRNFL)in children with type 1 diabetes without clinical diabetic retinopathy by optical coherence tomography angiography(OCTA),providing a basis for early retinopathy in children with type 1 diabetes.METHODS:This was a retrospective study.A total of 30 patients(3–14y)with type 1 diabetes without clinical diabetic retinopathy(NDR group)were included.A total of 30 age-matched healthy subjects were included as the normal control group(CON group).The HbA1c level in the last 3mo was measured once in the NDR group.The pRNFL thickness and ppVD were automatically measured,and the mean pRNFL and ppVD were calculated in the nasal,inferior,temporal,and superior quadrants.The changes in ppVD and pRNFL in the two groups were analyzed.RESULTS:Compared with CON group,the nasal and superior ppVDs decreased in the NDR group(all P<0.01).The thickness of the nasal pRNFL decreased significantly(P<0.01),while the inferior,temporal and superior pRNFLs slightly decreased but not significant in the NDR group(all P>0.05).Person and Spearman correlation analysis of ppVD and pRNFL thickness in each quadrant of the NDR group showed a positive correlation between nasal and superior(all P<0.01),while inferior and temporal had no significant correlation(all P>0.05).There was no significant correlation between the HbA1c level and ppVD and pRNFL in any quadrant(all P>0.05).There was no significant correlation between the course of diabetes mellitus and ppVD and pRNFL in any quadrant(all P>0.05).CONCLUSION:ppVD and pRNFL decrease in eyes of children with type 1 diabetes before clinically detectable retinopathy and OCTA is helpful for early monitoring.

Reduction of photodynamic damage of blood vessels in the protected region by(–)-epigallocatechin gallate

Photodynamic therapy(PDT)has been increasingly used in the clinical treatment of neoplastic,inflammatory and infectious skin diseases.However,the generation of reactive oxygen species(ROS)may induce undesired side effects in normal tissue surrounding the treatment lesion,which is a big challenge for the clinical application of PDT.To date,(–)-Epigallocatechin gallate(EGCG)has been widely proposed as an antiangiogenic and antitumor agent for the protection of normal tissue from ROS-mediated oxidative damage.This study evaluates the regulation ability of EGCG for photodynamic damage of blood vessels during hematoporphyrin monomethyl ether(Hemoporfin)-mediated PDT.The quenching rate constants of EGCG for the triplet-state Hemoporfin and photosensitized 1O2 generation are determined to be 6.8×10^(8)M^(−1)S^(−1),respectively.The vasoconstriction of blood vessels in the protected region treated with EGCG hydrogel after PDT is lower than that of the control region treated with pure hydrogel,suggesting an efficiently reduced photodamage of Hemoporfin for blood vessels treated with EGCG.This study indicates that EGCG is an efficient quencher for triplet-state Hemoporfin and 1O2,and EGCG could be potentially used to reduce the undesired photodamage of normal tissue in clinical PDT.

Cognitive impairment in cerebral small vessel disease induced by hypertension

Hypertension is a primary risk factor for the progression of cognitive impairment caused by cerebral small vessel disease,the most common cerebrovascular disease.Howeve r,the causal relationship between hypertension and cerebral small vessel disease remains unclear.Hypertension has substantial negative impacts on brain health and is recognized as a risk factor for cerebrovascular disease.Chronic hypertension and lifestyle factors are associated with risks for stro ke and dementia,and cerebral small vessel disease can cause dementia and stroke.Hypertension is the main driver of cerebral small vessel disease,which changes the structure and function of cerebral vessels via various mechanisms and leads to lacunar infarction,leukoaraiosis,white matter lesions,and intracerebral hemorrhage,ultimately res ulting in cognitive decline and demonstrating that the brain is the to rget organ of hypertension.This review updates our understanding of the pathogenesis of hypertensioninduced cerebral small vessel disease and the res ulting changes in brain structure and function and declines in cognitive ability.We also discuss drugs to treat cerebral small vessel disease and cognitive impairment.

Research and Design of Drop Keel System for Multi-purpose Oceanographic Vessel

当一个海洋学的容器正在航行时，轮船壳的表面附近的水流是快速的，使满足科学观察设备的环境要求难。保证安装空间和观察设备的环境要求，落下龙骨系统在中国为海洋图轮船第一次被建议，避免传统的赤睛鱼柄类型鳍龙骨劣势。研究学习将检验落下龙骨系统的运作的机制和函数，鳍的操作条件翻身决定驱动程序方法和它的安排，和鳍的锁住的方法翻身在水下。研究将也为为落下龙骨系统分析最好的计划提供一些一般图案。

Effects of Progressive Muscle Relaxation Training on Anxiety, Depression, and Quality of Life in Patients with Cerebral Small Vessel Disease

Objective:To explore the effects of progressive muscle relaxation training on anxiety,depression,and quality of life in patients with cerebral small vessel disease(CSVD).Methods:Sixty-one patients with CSVD in the Department of Neurology of a tertiary hospital were divided into an observation group(28 patients)and a control group(33 patients)by lottery method.The control group received conventional nursing care,while the observation group received progressive muscle relaxation training interventions in addition to the conventional care.The Hamilton Anxiety Scale(HAMA),the Hamilton Depression Scale(HAMD),and the Stroke-Specific Quality of Life Scale(SS-QOL)were used to compare the effects before the intervention,7 days after the intervention,and 30 days after the intervention.Results:Over time,at different time points after the intervention,the anxiety and depression scores of patients with CSVD in the observation group were significantly lower than those in the control group(P<0.05).The quality of life scores were significantly higher in the observation group compared to the control group(P<0.05),and these differences were statistically significant.Conclusion:Progressive muscle relaxation training can improve anxiety and depression in patients with cerebral small vessel disease and can effectively enhance their quality of life.

Using Stochastic Colored Petri nets for Designing Multi-Purpose Plants

Designing of a multi-purpose plant as one of the well-known manufacturing systems is more challenging than other manufacturing systems. This paper applies a stochastic colored Petri net (CPN) to design and analyze multi-purpose plants. A simple approach is proposed to determine the utilization of shared resources and to reduce the equipment’s idle times. Three scenarios are presented to describe the proposed model. Generally, according to desire of a decision maker, different scenarios can be considered in the model to achieve to the expected design or plant configuration. The main characteristics of the proposed model are flexibility, the easiness of practical application and the simulation of the model in an easy way.

Water Quality Assessment of the Owena Multi-Purpose Dam, Ondo State, Southwestern Nigeria

Composite water samples taken from Owena Multi-purpose Dam in six sampling campaigns covering the wet and dry seasons were analyzed for physico-chemical and microbial characteristics using standard methods for the examination of water and wastewater jointly published by the American Public Health Association, American Water Works Association and Water Pollution Control Federation. Results showed significant (p < 0.05) seasonal variations in most measured parameters with few showing significant spatial variation. The characteristics of the water from the dam lake revealed an acceptable quality for most measured parameters with low chemical pollutants burden when compared with drinking water standards and water quality for aquaculture. However, high values of turbidity, colour, iron, manganese and microbial load were recorded compared with drinking water standards, which call for proper treatment of the water before distribution for public consumption.

SepFE:Separable Fusion Enhanced Network for Retinal Vessel Segmentation

The accurate and automatic segmentation of retinal vessels fromfundus images is critical for the early diagnosis and prevention ofmany eye diseases,such as diabetic retinopathy(DR).Existing retinal vessel segmentation approaches based on convolutional neural networks(CNNs)have achieved remarkable effectiveness.Here,we extend a retinal vessel segmentation model with low complexity and high performance based on U-Net,which is one of the most popular architectures.In view of the excellent work of depth-wise separable convolution,we introduce it to replace the standard convolutional layer.The complexity of the proposed model is reduced by decreasing the number of parameters and calculations required for themodel.To ensure performance while lowering redundant parameters,we integrate the pre-trained MobileNet V2 into the encoder.Then,a feature fusion residual module(FFRM)is designed to facilitate complementary strengths by enhancing the effective fusion between adjacent levels,which alleviates extraneous clutter introduced by direct fusion.Finally,we provide detailed comparisons between the proposed SepFE and U-Net in three retinal image mainstream datasets(DRIVE,STARE,and CHASEDB1).The results show that the number of SepFE parameters is only 3%of U-Net,the Flops are only 8%of U-Net,and better segmentation performance is obtained.The superiority of SepFE is further demonstrated through comparisons with other advanced methods.

Automated Segmentation of the Brainstem,Cranial Nerves and Vessels for Trigeminal Neuralgia and Hemifacial Spasm

Accurate localization of cranial nerves and responsible blood vessels is important for diagnosing trigeminal neuralgia(TN)and hemifacial spasm(HFS).Manual delineation of the nerves and vessels on medical images is time-consuming and labor-intensive.Due to the development of convolutional neural networks(CNNs),the performance of medical image segmentation has been improved.In this work,we investigate the plans for automated segmentation of cranial nerves and responsible vessels for TN and HFS,which has not been comprehensively studied before.Different inputs are given to the CNN to find the best training configuration of segmenting trigeminal nerves,facial nerves,responsible vessels and brainstem,including the image modality and the number of segmentation targets.According to multiple experiments with seven training plans,we suggest training with the combination of three-dimensional fast imaging employing steady-state acquisition(3D-FIESTA)and three-dimensional time-of-flight magnetic resonance angiography(3DTOF-MRA),and separate segmentation of cranial nerves and vessels.

Bias Effects on the Reynolds Stress Using the Multi-Purpose Probe in IR-T1 Tokamak

The effect of the positive bias on Reynolds stress （RS） and its effect on the radial turbulent transport at the edge plasma （r/a =0.9） and scrape-off layer （SOL） region of plasma in tokamak are investigated. The radial and poloidal electric fields （Sr, Ep） and ion saturation current （Is） are measured by multi-purpose probe （MPP）. This probe is fabricated and constructed for the first time in the IR-T1 tokamak. The most advantage of this probe is that the variations of Er and Ep can be measured in different radii at the single shot. Thus the information of different radii can be compared with high precision. The bias voltage is fixed at Vbias = 200 V and it has been applied with the limiter bias that is fixed in r/a = 0.9. Moreover, the phase difference between radial and poloidal electric fields, and temporal evolution of the RS .spectrum detected by MPP are calculated. RS magnitude on the edge （r/a = 0.9） is more than its value in the SOL （r/a = 1.02）. With the applied bias 200 V, ItS and the magnitude of the phase difference between Er and Ep are increased, while the radial turbulent transport is decreased simultaneously. Thus it can be concluded that RS affects radial turbulence. Temporal evolution of the RS spectrum shows that the frequency of RS is increased and reaches its highest value at r/a=0.9 in the presence of bias.