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Prediction of Esophageal Varices in Viral Hepatitis C Cirrhosis: Performance of Combined Ultrasonography and Clinical Predictors. 病毒性丙型肝炎肝硬化食管静脉曲张的预测:联合超声检查和临床预测指标的表现。
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2023-09-15 eCollection Date: 2023-01-01 DOI: 10.1155/2023/7938732
Puwitch Charoenchue, Wittanee Na Chiangmai, Amonlaya Amantakul, Wasuwit Wanchaitanawong, Taned Chitapanarux, Suwalee Pojchamarnwiputh

Objectives: This study is aimed at evaluating the diagnostic performance of clinical predictors and the Doppler ultrasonography in predicting esophageal varices (EV) in patients with hepatitis C-related cirrhosis and exploring the practical predictors of EV.

Methods: We conducted a prospective study from July 2020 to January 2021, enrolling 65 patients with mild hepatitis C-related cirrhosis. We obtained clinical data and performed grayscale and the Doppler ultrasound to explore the predictors of EV. Esophagogastroduodenoscopy (EGD) was performed as the reference test by the gastroenterologist within a week.

Results: The prevalence of EV in the study was 41.5%. Multivariable regression analysis revealed that gender (female, OR = 4.04, p = 0.02), platelet count (<150000 per ml, OR = 3.13, p = 0.09), splenic length (>11 cm, OR = 3.64, p = 0.02), and absent right hepatic vein (RHV) triphasicity (OR = 3.15, p = 0.03) were significant predictors of EV. However, the diagnostic accuracy indices for isolated predictors were not good (AUROC = 0.63-0.66). A combination of these four predictors increases the diagnostic accuracy in predicting the presence of EV (AUROC = 0.80, 95% CI 0.69-0.91). Furthermore, the Doppler assessment of the right hepatic vein waveform showed good reproducibility (κ = 0.76).

Conclusion: Combining clinical and Doppler ultrasound features can be used as a screening test for predicting the presence of EV in patients with hepatitis C-related cirrhosis. The practical predictors identified in this study could serve as an alternative to invasive EGD in EV diagnosis. Further studies are needed to explore the diagnostic accuracy of additional noninvasive predictors, such as elastography, to improve EV screening.

目的:本研究旨在评估临床预测指标和多普勒超声在预测丙型肝炎相关肝硬化患者食管静脉曲张(EV)方面的诊断性能,并探索EV的实用预测指标。方法:我们于2020年7月至2021年1月进行了一项前瞻性研究,纳入65名轻度丙型肝炎相关肝硬变患者。我们获得了临床数据,并进行了灰阶和多普勒超声检查,以探索EV的预测因素。胃肠科医生在一周内进行了食管胃十二指肠镜检查(EGD)作为参考测试。结果:研究中EV的患病率为41.5%。多因素回归分析显示,性别(女性,OR=4.04,p=0.02)、血小板计数(p=0.09)、脾脏长度(>11 cm,OR=3.64,p=0.02)和无右肝静脉(RHV)三相性(OR=3.15,p=0.03)是EV的显著预测因素。然而,单独预测因素的诊断准确性指数不好(AUROC=0.63-0.66)。这四个预测因素的组合提高了预测EV存在的诊断准确性(AUROC=0.80,95%CI 0.69-0.91)。此外,结论:结合临床和多普勒超声特征,可以作为预测丙型肝炎相关肝硬化患者EV存在的筛查试验。本研究中确定的实用预测因子可作为EV诊断中侵入性EGD的替代方案。需要进一步的研究来探索其他非侵入性预测因子的诊断准确性,如弹性成像,以改进EV筛查。
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引用次数: 0
Multiparametric Magnetic Resonance Imaging and Magnetic Resonance Elastography to Evaluate the Early Effects of Bariatric Surgery on Nonalcoholic Fatty Liver Disease. 多参数磁共振成像和磁共振弹性成像评估减肥手术对非酒精性脂肪性肝病的早期影响。
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2023-01-01 DOI: 10.1155/2023/4228321
Hong Chang Tan, Elizabeth Shumbayawonda, Cayden Beyer, Lionel Tim-Ee Cheng, Albert Low, Chin Hong Lim, Alvin Eng, Weng Hoong Chan, Phong Ching Lee, Mei Fang Tay, Stella Kin, Jason Pik Eu Chang, Yong Mong Bee, George Boon Bee Goh

Background: Bariatric surgery is the most effective treatment for morbid obesity and reduces the severity of nonalcoholic fatty liver disease (NAFLD) in the long term. Less is known about the effects of bariatric surgery on liver fat, inflammation, and fibrosis during the early stages following bariatric surgery.

Aims: This exploratory study utilises advanced imaging methods to investigate NAFLD and fibrosis changes during the early metabolic transitional period following bariatric surgery.

Methods: Nine participants with morbid obesity underwent sleeve gastrectomy. Multiparametric MRI (mpMRI) and magnetic resonance elastography (MRE) were performed at baseline, during the immediate (1 month), and late (6 months) postsurgery period. Liver fat was measured using proton density fat fraction (PDFF), disease activity using iron-correct T1 (cT1), and liver stiffness using MRE. Repeated measured ANOVA was used to assess longitudinal changes and Dunnett's method for multiple comparisons.

Results: All participants (Age 45.1 ± 9.0 years, BMI 39.7 ± 5.3 kg/m2) had elevated hepatic steatosis at baseline (PDFF >5%). In the immediate postsurgery period, PDFF decreased significantly from 14.1 ± 7.4% to 8.9 ± 4.4% (p = 0.016) and cT1 from 826.9 ± 80.6 ms to 768.4 ± 50.9 ms (p = 0.047). These improvements continued to the later postsurgery period. Bariatric surgery did not reduce liver stiffness measurements.

Conclusion: Our findings support using MRI as a noninvasive tool to monitor NAFLD in patient with morbid obesity during the early stages following bariatric surgery.

背景:减肥手术是治疗病态肥胖最有效的方法,并能长期降低非酒精性脂肪性肝病(NAFLD)的严重程度。在减肥手术后的早期阶段,减肥手术对肝脏脂肪、炎症和纤维化的影响尚不清楚。目的:本探索性研究利用先进的成像方法研究减肥手术后早期代谢过渡期NAFLD和纤维化的变化。方法:9例病态肥胖患者行袖式胃切除术。在基线、术后即刻(1个月)和后期(6个月)分别进行多参数MRI (mpMRI)和磁共振弹性成像(MRE)检查。使用质子密度脂肪分数(PDFF)测量肝脏脂肪,使用铁校正T1 (cT1)测量疾病活动性,使用MRE测量肝脏硬度。采用重复测量方差分析评估纵向变化,采用Dunnett法进行多重比较。结果:所有参与者(年龄45.1±9.0岁,BMI 39.7±5.3 kg/m2)在基线时肝脏脂肪变性升高(PDFF >5%)。术后即刻PDFF由14.1±7.4%降至8.9±4.4% (p = 0.016), cT1由826.9±80.6 ms降至768.4±50.9 ms (p = 0.047)。这些改善持续到手术后期。减肥手术没有降低肝脏硬度测量值。结论:我们的研究结果支持使用MRI作为一种无创工具来监测减肥手术后早期病态肥胖患者的NAFLD。
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引用次数: 0
Enhanced Extraction of Blood and Tissue Time-Activity Curves in Cardiac Mouse FDG PET Imaging by Means of Constrained Nonnegative Matrix Factorization. 约束非负矩阵分解增强提取心脏小鼠FDG PET成像血液和组织时间-活性曲线。
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2023-01-01 DOI: 10.1155/2023/5366733
Otman Sarrhini, Pedro D'Orléans-Juste, Jacques A Rousseau, Jean-François Beaudoin, Roger Lecomte

We propose an enhanced method to accurately retrieve time-activity curves (TACs) of blood and tissue from dynamic 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET) cardiac images of mice. The method is noninvasive and consists of using a constrained nonnegative matrix factorization algorithm (CNMF) applied to the matrix (A) containing the intensity values of the voxels of the left ventricle (LV) PET image. CNMF factorizes A into nonnegative matrices H and W, respectively, representing the physiological factors (blood and tissue) and their associated weights, by minimizing an extended cost function. We verified our method on 32 C57BL/6 mice, 14 of them with acute myocardial infarction (AMI). With CNMF, we could break down the mouse LV into myocardial and blood pool images. Their corresponding TACs were used in kinetic modeling to readily determine the [18F]FDG influx constant (Ki) required to compute the myocardial metabolic rate of glucose. The calculated Ki values using CNMF for the heart of control mice were in good agreement with those published in the literature. Significant differences in Ki values for the heart of control and AMI mice were found using CNMF. The values of the elements of W agreed well with the LV structural changes induced by ligation of the left coronary artery. CNMF was compared with the recently published method based on robust unmixing of dynamic sequences using regions of interest (RUDUR). A clear improvement of signal separation was observed with CNMF compared to the RUDUR method.

我们提出了一种增强的方法,可以准确地从小鼠动态2-脱氧-2-[18F]氟-d -葡萄糖([18F]FDG)正电子发射断层扫描(PET)心脏图像中检索血液和组织的时间-活性曲线(tac)。该方法是非侵入性的,使用约束非负矩阵分解算法(CNMF)应用于包含左心室(LV) PET图像体素强度值的矩阵(a)。CNMF通过最小化扩展成本函数,将A分解为非负矩阵H和W,分别表示生理因素(血液和组织)及其相关权重。我们在32只C57BL/6小鼠身上验证了我们的方法,其中14只患有急性心肌梗死(AMI)。利用CNMF,我们可以将小鼠左室分解成心肌和血池图像。将它们对应的tac用于动力学建模,以方便地确定计算心肌葡萄糖代谢率所需的[18F]FDG内流常数(Ki)。使用CNMF计算的对照小鼠心脏Ki值与文献中发表的值一致。使用CNMF发现对照组和AMI小鼠心脏的Ki值有显著差异。W元素值与左冠状动脉结扎引起的左室结构改变吻合较好。将CNMF与最近发表的基于感兴趣区域(RUDUR)的动态序列鲁棒解混方法进行了比较。与RUDUR方法相比,CNMF方法明显改善了信号分离。
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引用次数: 2
In Vivo Fluorine Imaging Using 1.5 Tesla MRI for Depiction of Experimental Myocarditis in a Rodent Animal Model. 使用1.5特斯拉磁共振成像在体内氟成像描绘实验性心肌炎在啮齿动物模型。
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2023-01-01 DOI: 10.1155/2023/4659041
Thore Dietrich, Stephan Theodor Bujak, Thorsten Keller, Bernhard Schnackenburg, Riad Bourayou, Rolf Gebker, Kristof Graf, Eckart Fleck

The usefulness of perfluorocarbon nanoemulsions for the imaging of experimental myocarditis has been demonstrated in a high-field 9.4 Tesla MRI scanner. Our proof-of-concept study investigated the imaging capacity of PFC-based 19F/1H MRI in an animal myocarditis model using a clinical field strength of 1.5 Tesla. To induce experimental myocarditis, five male rats (weight ~300 g, age ~50 days) were treated with one application per week of doxorubicin (2 mg/kg BW) over a period of six weeks. Three control animals received the identical volume of sodium chloride 0.9% instead. Following week six, all animals received a single 4 ml injection of an 20% oil-in-water perfluorooctylbromide nanoemulsion 24 hours prior to in vivo1H/19F imaging on a 1.5 Tesla MRI. After euthanasia, cardiac histology and immunohistochemistry using CD68/ED1 macrophage antibodies were performed, measuring the inflamed myocardium in μm2 for further statistical analysis to compare the extent of the inflammation with the 19F-MRI signal intensity. All animals treated with doxorubicin showed a specific signal in the myocardium, while no myocardial signal could be detected in the control group. Additionally, the doxorubicin group showed a significantly higher SNR for 19F and a stronger CD68/ED1 immunhistoreactivity compared to the control group. This proof-of-concept study demonstrates that perfluorocarbon nanoemulsions could be detected in an in vivo experimental myocarditis model at a currently clinically relevant field strength.

全氟碳纳米乳对实验性心肌炎成像的有用性已在高场9.4特斯拉MRI扫描仪中得到证实。我们的概念验证研究考察了基于pfc的19F/1H MRI在动物心肌炎模型中使用1.5特斯拉临床场强的成像能力。为了诱导实验性心肌炎,将5只体重~300 g、年龄~50日龄的雄性大鼠,每周1次给予阿霉素(2 mg/kg BW),持续6周。而对照组的三只动物则注射了相同体积的0.9%氯化钠。第六周后,所有动物在1.5特斯拉MRI 1h /19F成像前24小时接受单次4 ml 20%水包油全氟辛基溴纳米乳注射。安乐死后采用CD68/ED1巨噬细胞抗体进行心脏组织学和免疫组化,以μm2为单位测量炎症心肌,进一步统计分析炎症程度与19F-MRI信号强度的比较。阿霉素处理的所有动物心肌均有特异信号,而对照组未检测到心肌信号。此外,与对照组相比,阿霉素组显示出更高的19F信噪比和更强的CD68/ED1免疫组化活性。这项概念验证研究表明,全氟碳纳米乳剂可以在体内实验心肌炎模型中以当前临床相关的场强检测到。
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引用次数: 0
Chest X-Ray Images to Differentiate COVID-19 from Pneumonia with Artificial Intelligence Techniques. 利用人工智能技术通过胸部 X 光图像区分 COVID-19 和肺炎
IF 3.3 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2022-12-22 eCollection Date: 2022-01-01 DOI: 10.1155/2022/5318447
Rumana Islam, Mohammed Tarique

This paper presents an automated and noninvasive technique to discriminate COVID-19 patients from pneumonia patients using chest X-ray images and artificial intelligence. The reverse transcription-polymerase chain reaction (RT-PCR) test is commonly administered to detect COVID-19. However, the RT-PCR test necessitates person-to-person contact to administer, requires variable time to produce results, and is expensive. Moreover, this test is still unreachable to the significant global population. The chest X-ray images can play an important role here as the X-ray machines are commonly available at any healthcare facility. However, the chest X-ray images of COVID-19 and viral pneumonia patients are very similar and often lead to misdiagnosis subjectively. This investigation has employed two algorithms to solve this problem objectively. One algorithm uses lower-dimension encoded features extracted from the X-ray images and applies them to the machine learning algorithms for final classification. The other algorithm relies on the inbuilt feature extractor network to extract features from the X-ray images and classifies them with a pretrained deep neural network VGG16. The simulation results show that the proposed two algorithms can extricate COVID-19 patients from pneumonia with the best accuracy of 100% and 98.1%, employing VGG16 and the machine learning algorithm, respectively. The performances of these two algorithms have also been collated with those of other existing state-of-the-art methods.

本文介绍了一种利用胸部 X 光图像和人工智能区分 COVID-19 患者和肺炎患者的自动化、无创技术。逆转录聚合酶链反应(RT-PCR)测试是检测 COVID-19 的常用方法。然而,RT-PCR 检测需要人与人之间的接触才能进行,产生结果所需的时间不固定,而且价格昂贵。此外,这种检测方法仍无法惠及全球大量人口。胸部 X 光图像在这方面可以发挥重要作用,因为任何医疗机构都有 X 光机。然而,COVID-19 和病毒性肺炎患者的胸部 X 光图像非常相似,往往会导致主观误诊。这项研究采用了两种算法来客观地解决这一问题。一种算法使用从 X 光图像中提取的低维编码特征,并将其应用于机器学习算法进行最终分类。另一种算法则依靠内置的特征提取器网络从 X 光图像中提取特征,并通过预训练的深度神经网络 VGG16 进行分类。仿真结果表明,采用 VGG16 和机器学习算法,所提出的两种算法可将 COVID-19 患者从肺炎中解救出来,准确率分别达到 100%和 98.1%。这两种算法的性能还与其他现有的先进方法进行了比较。
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引用次数: 0
Relative Perfusion Differences between Parathyroid Adenomas and the Thyroid on Multiphase 4DCT 甲状旁腺腺瘤和甲状腺在多期4DCT上的相对灌注差异
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2022-05-20 DOI: 10.1155/2022/2984789
S. Raeymaeckers, Yannick De Brucker, Maurizio Tosi, N. Buls, J. Mey
A multiphase 4DCT technique can be useful for the detection of parathyroid adenomas. Up to 16 different phases can be obtained without significant increase of exposure dose using wide beam axial scanning. This technique also allows for the calculation of perfusion parameters in suspected lesions. We present data on 19 patients with histologically proven parathyroid adenomas. We find a strong correlation between 2 perfusion parameters when comparing parathyroid adenomas and thyroid tissue: parathyroid adenomas show a 55% increase in blood flow (BF) (p < 0.001) and a 50% increase in blood volume (BV) (p < 0.001) as compared to normal thyroid tissue. The analysis of the ROC curve for the different perfusion parameters demonstrates a significantly high area under the curve for BF and BV, confirming these two perfusion parameters to be a possible discriminating tool to discern between parathyroid adenomas and thyroid tissue. These findings can help to discern parathyroid from thyroid tissue and may aid in the detection of parathyroid adenomas.
多期4DCT技术可用于甲状旁腺瘤的检测。使用宽束轴向扫描可以在不显著增加暴露剂量的情况下获得多达16个不同的相位。该技术还可以计算疑似病变的灌注参数。我们报告了19例经组织学证实的甲状旁腺瘤患者的资料。当比较甲状旁腺腺瘤和甲状腺组织时,我们发现两个灌注参数之间有很强的相关性:与正常甲状腺组织相比,甲状旁腺瘤的血流量(BF)增加55% (p < 0.001),血容量(BV)增加50% (p < 0.001)。不同灌注参数的ROC曲线分析显示BF和BV的曲线下面积明显高,证实这两个灌注参数可能是区分甲状旁腺瘤和甲状腺组织的鉴别工具。这些发现有助于从甲状腺组织中区分甲状旁腺,并可能有助于甲状旁腺瘤的检测。
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引用次数: 1
MRI Reconstruction with Separate Magnitude and Phase Priors Based on Dual-Tree Complex Wavelet Transform 基于对偶树复小波变换的分离幅度和相位先验的MRI重建
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2022-04-29 DOI: 10.1155/2022/7251674
W. He, Linman Zhao
The methods of compressed sensing magnetic resonance imaging (CS-MRI) can be divided into two categories roughly based on the number of target variables. One group devotes to estimating the complex-valued MRI image. And the other calculates the magnitude and phase parts of the complex-valued MRI image, respectively, by enforcing separate penalties on them. We propose a new CS-based method based on dual-tree complex wavelet (DT CWT) sparsity, which is under the frame of the second class of CS-MRI. Owing to the separate regularization frame, this method reduces the impact of the phase jumps (that means the jumps or discontinuities of phase values) on magnitude reconstruction. Moreover, by virtue of the excellent features of DT CWT, such as nonoscillating envelope of coefficients and multidirectional selectivity, the proposed method is capable of capturing more details in the magnitude and phase images. The experimental results show that the proposed method recovers the image contour and edges information well and can eliminate the artifacts in magnitude results caused by phase jumps.
压缩传感磁共振成像(CS-MRI)的方法大致可以根据目标变量的数量分为两类。一组致力于估计复值MRI图像。另一个通过对复值MRI图像执行单独的惩罚,分别计算它们的幅度和相位部分。在第二类CS-MRI的框架下,我们提出了一种基于对偶树复小波稀疏性的新的CS方法。由于独立的正则化框架,该方法减少了相位跳跃(即相位值的跳跃或不连续)对幅度重建的影响。此外,由于DT CWT的优异特性,如系数的非振荡包络和多向选择性,该方法能够在幅度和相位图像中捕捉更多细节。实验结果表明,该方法能很好地恢复图像的轮廓和边缘信息,并能消除相位跳跃引起的幅度结果中的伪影。
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引用次数: 0
Content-Based Image Retrieval Using Colour, Gray, Advanced Texture, Shape Features, and Random Forest Classifier with Optimized Particle Swarm Optimization 基于颜色、灰度、高级纹理、形状特征和具有优化粒子群优化的随机森林分类器的内容图像检索
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2022-04-21 DOI: 10.1155/2022/3211793
Dr. MANOHARAN SUBRAMANIAN, Velmurugan Lingamuthu, Chandran Venkatesan, S. Perumal
In this paper, a new approach for Content-Based Image Retrieval (CBIR) has been addressed by extracting colour, gray, advanced texture, and shape features for input query images. Contour-based shape feature extraction methods and image moment extraction techniques are used to extract the shape features and shape invariant features. The informative features are selected from extracted features and combined colour, gray, texture, and shape features by using PSO. The target image has been retrieved for the given query image by training the random forest classifier. The proposed colour, gray, advanced texture, shape feature, and random forest classifier with optimized PSO (CGATSFRFOPSO) provide efficient retrieval of images in a large-scale database. The main objective of this research work is to improve the efficiency and effectiveness of the CBIR system by extracting the features like colour, gray, texture, and shape from database images and query images. These extracted features are processed in various levels like removing redundancy by optimal feature selection and fusion by optimal weighted linear combination. The Particle Swarm Optimization algorithm is used for selecting the informative features from gray and colour and texture features. The matching accuracy and the speed of image retrieval are improved by an ensemble of machine learning algorithms for the similarity search.
本文提出了一种基于内容的图像检索(CBIR)的新方法,即提取输入查询图像的颜色、灰度、高级纹理和形状特征。采用基于轮廓的形状特征提取方法和图像矩提取技术提取形状特征和形状不变特征。利用粒子群算法从提取的特征中选择信息特征,并结合颜色、灰度、纹理和形状特征。通过训练随机森林分类器,对给定的查询图像检索到目标图像。提出的颜色、灰度、高级纹理、形状特征和随机森林分类器与优化的粒子群算法(CGATSFRFOPSO)提供了大规模数据库中图像的高效检索。本研究的主要目的是通过从数据库图像和查询图像中提取颜色、灰度、纹理、形状等特征,提高CBIR系统的效率和有效性。对提取的特征进行最优特征选择去除冗余和最优加权线性组合融合等不同层次的处理。采用粒子群算法从灰度、颜色和纹理特征中选择信息特征。通过对相似度搜索的机器学习算法的集成,提高了匹配精度和图像检索速度。
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引用次数: 4
Modified Gray-Level Haralick Texture Features for Early Detection of Diabetes Mellitus and High Cholesterol with Iris Image 改进灰度Haralick纹理特征用于虹膜图像早期检测糖尿病和高胆固醇
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2022-04-20 DOI: 10.1155/2022/5336373
R. K. Hapsari, Miswanto, R. Rulaningtyas, H. Suprajitno, H. Gan
Iris has specific advantages, which can record all organ conditions, body construction, and psychological disorders. Traces related to the intensity or deviation of organs caused by the disease are recorded systematically and patterned on the iris and its surroundings. The pattern that appears on the iris can be recognized by using image processing techniques. Based on the pattern in the iris image, this paper aims to provide an alternative noninvasive method for the early detection of DM and HC. In this paper, we perform detection based on iris images for two diseases, DM and HC simultaneously, by developing the invariant Haralick feature on quantized images with 256, 128, 64, 32, and 16 gray levels. The feature extraction process does early detection based on iris images. Researchers and scientists have introduced many methods, one of which is the feature extraction of the gray-level co-occurrence matrix (GLCM). Early detection based on the iris is done using the volumetric GLCM development, namely, 3D-GLCM. Based on 3D-GLCM, which is formed at a distance of d = 1 and in the direction of 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315°, it is used to calculate Haralick features and develop Haralick features which are invariant to the number of quantization gray levels. The test results show that the invariant feature with a gray level of 256 has the best identification performance. In dataset I, the accuracy value is 97.92, precision is 96.88, and recall is 95.83, while in dataset II, the accuracy value is 95.83, precision is 89.69, and recall is 91.67. The identification of DM and HC trained on invariant features showed higher accuracy than the original features.
虹膜具有特定的优势,可以记录所有器官状况、身体结构和心理障碍。与疾病引起的器官强度或偏差有关的痕迹被系统地记录下来,并在虹膜及其周围形成图案。虹膜上出现的图案可以通过使用图像处理技术来识别。基于虹膜图像中的模式,本文旨在为糖尿病和HC的早期检测提供一种替代的非侵入性方法。在本文中,我们通过在具有256、128、64、32和16灰度级的量化图像上发展不变的Haralick特征,同时基于虹膜图像对DM和HC这两种疾病进行检测。特征提取过程基于虹膜图像进行早期检测。研究人员和科学家已经介绍了许多方法,其中之一是灰度共生矩阵(GLCM)的特征提取。基于虹膜的早期检测是使用体积GLCM开发完成的,即3D-GLCM。基于距离d=1、方向为0°、45°、90°、135°、180°、225°、270°和315°的3D-GLCM,它被用来计算Haralick特征,并发展出对量化灰度级数量不变的Haralick特性。测试结果表明,灰度为256的不变特征具有最好的识别性能。在数据集I中,准确度值为97.92,准确度为96.88,召回率为95.83;而在数据集II中,准确率值为95.83,准确度89.69,召回率91.67。在不变特征上训练的DM和HC的识别显示出比原始特征更高的精度。
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引用次数: 1
Value CMR: Towards a Comprehensive, Rapid, Cost-Effective Cardiovascular Magnetic Resonance Imaging. 价值CMR:迈向全面、快速、高性价比的心血管磁共振成像。
IF 7.6 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2021-01-01 DOI: 10.1155/2021/8851958
El-Sayed H Ibrahim, Luba Frank, Dhiraj Baruah, V Emre Arpinar, Andrew S Nencka, Kevin M Koch, L Tugan Muftuler, Orhan Unal, Jadranka Stojanovska, Jason C Rubenstein, Sherry-Ann Brown, John Charlson, Elizabeth M Gore, Carmen Bergom

Cardiac magnetic resonance imaging (CMR) is considered the gold standard for measuring cardiac function. Further, in a single CMR exam, information about cardiac structure, tissue composition, and blood flow could be obtained. Nevertheless, CMR is underutilized due to long scanning times, the need for multiple breath-holds, use of a contrast agent, and relatively high cost. In this work, we propose a rapid, comprehensive, contrast-free CMR exam that does not require repeated breath-holds, based on recent developments in imaging sequences. Time-consuming conventional sequences have been replaced by advanced sequences in the proposed CMR exam. Specifically, conventional 2D cine and phase-contrast (PC) sequences have been replaced by optimized 3D-cine and 4D-flow sequences, respectively. Furthermore, conventional myocardial tagging has been replaced by fast strain-encoding (SENC) imaging. Finally, T1 and T2 mapping sequences are included in the proposed exam, which allows for myocardial tissue characterization. The proposed rapid exam has been tested in vivo. The proposed exam reduced the scan time from >1 hour with conventional sequences to <20 minutes. Corresponding cardiovascular measurements from the proposed rapid CMR exam showed good agreement with those from conventional sequences and showed that they can differentiate between healthy volunteers and patients. Compared to 2D cine imaging that requires 12-16 separate breath-holds, the implemented 3D-cine sequence allows for whole heart coverage in 1-2 breath-holds. The 4D-flow sequence allows for whole-chest coverage in less than 10 minutes. Finally, SENC imaging reduces scan time to only one slice per heartbeat. In conclusion, the proposed rapid, contrast-free, and comprehensive cardiovascular exam does not require repeated breath-holds or to be supervised by a cardiac imager. These improvements make it tolerable by patients and would help improve cost effectiveness of CMR and increase its adoption in clinical practice.

心脏磁共振成像(CMR)被认为是测量心功能的金标准。此外,在单次CMR检查中,可以获得有关心脏结构、组织组成和血流的信息。然而,由于扫描时间长、需要多次屏气、使用造影剂以及相对较高的成本,CMR尚未得到充分利用。在这项工作中,我们提出了一种快速,全面,无对比度的CMR检查,不需要重复屏气,基于成像序列的最新发展。在拟议的CMR考试中,耗时的传统序列已被高级序列所取代。具体来说,传统的2D电影和相衬(PC)序列分别被优化的3d电影和4d流序列所取代。此外,传统的心肌标记已被快速菌株编码(SENC)成像所取代。最后,T1和T2定位序列包括在拟议的检查中,这允许心肌组织表征。提出的快速检查已经在体内进行了测试。该检测方法将扫描时间从传统序列的>1小时缩短到
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引用次数: 5
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International Journal of Biomedical Imaging
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