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This study is aimed at assessing the ecological risk of heavy metals (HMs) in the International Hamoun wetland, southeastern Iran. Twenty sediment samples were collected from the wetland surface for geochemical analysis of 23 HMs. The inverse distance weighting (IDW) technique was used to map the HMs. The single and multi-element pollution indicators and PER index (PERI) were respectively used to determine the contamination intensity and PER level. The principal components analysis (PCA) was performed to identify the HM source. The mean concentration of cesium (Cs: 5.2 µg/g), selenium (Se: 0.9 µg/g), and tellurium (Te: 0.2 µg/g) was higher than their mean values in the Earth's crust. The enrichment factor (EF) showed the Hamoun was high to extremely enriched by Te, As, and Se. The geo-accumulation index (GeoI) revealed the highest level of contamination caused by As, barium (Ba), cobalt (Co), chromium (Cr), cuprum (Cu), ferrum (Fe), manganese (Mn), nickel (Ni), lead (Pb), rubidium(Rb), titanium (Ti), vanadium(V), yttrium (Y), and zinc (Zn) in most study sites. The sediment contamination factor in more than 55% of the sediment samples was between 8 and 16, indicating very high contamination intensity in the studied wetland. The PER values were between 80 and 160 in more than 60% of the sediment samples, suggesting a considerable risk in the wetland. The PCA showed both anthropogenic and crustal activities were effective in increasing the concentration of HMs in the wetland. The largest ecological risk was due to arsenic (As) and cadmium (Cd). It is recommended to pay more attention to these HMs, which could cause more environmental pollution in the International Hamoun wetland, southeastern Iran., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Competing Interests: Authors' Disclosures of Potential Conflicts of Interest: No potential conflicts of interest relevant to this article were reported.

The quantitative analysis of cardiac motion from echocardiographic images helps clinicians in the diagnosis and therapy of patients suffering from heart disease. Quantitative analysis is usually based on tissue Doppler imaging (TDI) or speckle tracking. These methods are based on two techniques which to a large degree are independent: the Doppler phenomenon and image sequence processing. Herein, to increase the accuracy of the speckle tracking technique and to cope with the angle dependence of TDI, a combined approach dubbed tissue Doppler imaging optical flow (TDIOF) is proposed. TDIOF is formulated based on the combination of B-mode and Doppler energy terms minimized using algebraic equations and is validated on simulated images, and in vivo data. It was observed that the additional Doppler term is able to increase the accuracy of speckle tracking, compared to two popular motion estimation and speckle tracking techniques (Horn-Schunck and block matching methods). This observation was more pronounced when noise was present. The magnitude and angular error for TDIOF applied to simulated images, when comparing estimated motion with ground-truth motion, were 15% and 9.2°/frame, respectively. As an additional validation, echocardiography-derived strains were compared to tagged MRI-derived myocardial strains in the same subjects. The correlation coefficient (r) between the TDIOF-derived radial strains and tagged MRI-derived radial strains value was 0.83 (P < 0.001). The correlation coefficient ( r) for the TDIOF-derived circumferential strains compared to the tagged MRI-derived circumferential strains was 0.86 (P < 0.001). The comparison of TDIOF-derived and block matching speckle tracking and Horn-Schunck optical flow strain values using student t-test demonstrated superiority of TDIOF (95% confidence interval, P < 0.001).

Objective: The objective of this study is to determine the normal value of 3D left ventricular (LV) twist in subendocardial, mid-wall and subepicardial layers, as well as to study the effects of aging on 3D LV twist by tagged MR motion tracking techniques. Three dimensional motion detection based on 3D tagged MR images is robust to out-of-plane motion error; while 2D motion detection is inherently unable to analyze the 3D cardiac motion and may lead to inaccurate results., Methods: The 3D LV volumetric images were acquired in 52 normal adult subjects (aged 21-82) and were analyzed by using 3D HARmonic phase (HARP) technique. HARP technique provided the 3D displacement fields and the displacements were utilized to compute the rotational values. LV twist was defined as apical rotation relative to the basal rotation, in the 3D coordinates. The LV twist values of subendocardial, mid-wall and subepicardial layers were analyzed separately. The measured parameters in this study were: peak apical rotation, peak basal rotation, and peak LV twist., Result: Looking at the apex, the normal LV maintains a clockwise rotation in the LV basal plane and a counterclockwise rotation in the LV apical plane. In general, the apical and basal rotation values increase during the aging process, leading to an increased value of LV twist. Peak epicardial LV twist is (10.4±2.6 degrees) which is lower than the mid-wall LV twist (11.3±2.2 degrees) and endocardial LV twist (12.1±2.6 degrees) in the young group (21-35 years old). Also, peak epicardial LV twist is (12.2±2.6 degrees) which is lower than the mid-wall LV twist (14.4±2.8 degrees) and endocardial LV twist (14.7±2.5 degrees) in the middle aged group (21-35 years old). In a similar way, peak epicardial LV twist is (14.8±2.9 degrees) which is lower than the mid-wall LV twist (15.7±3.6 degrees) and endocardial LV twist (16.7±3.0 degrees) in the old group (50-65 years old). Regarding the older group (more than 65 years old), peak epicardial LV twist is (15.9±3.1 degrees) which is lower than the mid-wall LV twist (16.2±3.4 degrees) and endocardial LV twist (18.3±3.0 degrees)., Conclusions: It is feasible to measure the subepicardial, mid-wall and subendocardial twist in tagged MR images. The twist value gradually increases in the aging process. Outside layers have greater twist values compared to the inside layers.

Ischemic heart disease is a leading cause of death in the modern world. Coronary obstruction is the basis for ischemic heart disease and leads to decreased cardiac supply and decreased contractility of the myocardium. Recently, high quality 4D computed tomography (CT) has become available for cardiac imaging and provides the clinician with high quality anatomical images. In this article, a new method is proposed to detect 3D motion and strain from 4D cardiac CT images by constraining intensity constancy, myocardial volume changes and motion smoothness assumptions. The proposed method is validated by using manual tracking of the cardiac CT landmarks. The average error for the manual tracking, by an expert, was 2.9 ± 0.9 mm. As an additional validation, the cardiac CT strain values were compared to the cardiac tagged magnetic resonance imaging (MRI) and 2D B-mode echocardiography strain values of the same patients. The correlation ratio was significantly high for CT and tagged MRI radial strain values (r = 0.76, 95% confidence interval, P < 0.001). The correlation ratio was meaningful for CT and echocardiography radial strain values as well (r = 0.67, 95% confidence interval, P < 0.001). The correlation ratio for CT and tagged MRI circumferential strain values was acceptable (r = 0.73, 95% confidence interval, P < 0.001), while the correlation ratio for CT and echocardiography circumferential strain values was good as well (r = 0.61, 95% confidence interval, P < 0.001). In general, motion and strain values computed from cardiac CT images agree with motion and strain values computed from tagged MRI and echocardiography images.

Objectives: The purpose of this study was to determine the normal value of left ventricular (LV) twist in 3-dimensional (3D) geometry and to study the effects of aging on 3D LV twist by sophisticated newly developed 3D speckle-tracking echocardiographic techniques., Methods: Recent developments in miniaturized ultrasound arrays have provided us with high-quality 3D echocardiographic data. Speckle tracking based on 3D images is robust to out-of-plane motion error, whereas 2-dimensional speckle tracking is inherently unable to analyze 3D cardiac motion and may lead to measurement inaccuracies. Three-dimensional LV volumetric images were acquired from 124 healthy volunteers (aged 21-82 years) and were analyzed by a recent speckle-tracking method. Left ventricular twist was analyzed as apical rotation relative to the base in the 3D coordinates. The measured parameters in this study were peak apical rotation, peak basal rotation, peak LV twist, normalized peak LV twist, and peak untwist velocity., Results: As seen from the apex, the normal LV maintains a wringing systolic displacement with an initial counterclockwise rotation followed by a clockwise rotation in the LV basal plane and a counterclockwise rotation in the LV apical plane. In general, the apical and basal twist increases during the aging process, leading to an increased LV twist value. The mean peak twist ± SD in young participants (21-35 years) was 11.73° ± 2.67°, whereas the value for older participants (>65 years) was 18.57° ± 3.08° (P < .001)., Conclusions: Three-dimensional speckle-tracking echocardiography can be an effective noninvasive method for assessing 3D LV twist. Age-related differences in the 3D LV twist may be the result of the age-related changes in the endocardial myofibers.

A cardiac phantom can be of crucial importance in the development and validation of ultrasound and cardiac magnetic resonance (MR) imaging and image analysis methods. A biventricular multimodal cardiac phantom has been manufactured in-house that can simulate normal and pathologic hearts with different degrees of infarction. The two-chamber structure can simulate the asymmetric left ventricular motion. Poly Vinyl Alcohol (PVA) is utilized as the basic material since it can simulate the shape, elasticity, and MR and ultrasound properties of the heart. The cardiac shape is simulated using a two-chamber acrylic mold. An additional pathologic heart phantom has been built to simulate aneurysm and infarction. Segmental dyskinesis is modeled based on three inclusions of different shapes and different degrees of elasticity. The cardiac elasticity is adjusted based on freeze-thaw cycles of the PVA cryogel for normal and scarred regions.

Objective: Noninvasive real-time thermal change monitoring of human internal organs can play a critical role in diagnosis and treatment of many disorders, including reperfusion of renal arteries during anticoagulation therapy., Methods: This article focuses on tissue temperature detection using ultrasound velocity changes in different structures and their related speckle shift from their primary locations on high-quality B-mode digital sonography. We evaluated different speckle-tracking techniques and optimized them using appropriate motion estimation methods to determine the best algorithm and parameters., Results: Performing thermal detection methods on simulated phantoms showed a good correlation between speckle shifts and the ground truth temperature. For the simulated images, average thermal error was 0.5 degrees C with an SD of 0.5 degrees C, where lower errors can be obtained in noiseless (motionless) data. The proposed technique was evaluated on real in vivo cases during surgical occlusion and reopening of the renal segmental artery and showed the potential of the algorithm for observation of internal organ changes using only digital ultrasound systems for diagnosis and therapy., Conclusions: The adaptive Rood pattern search proved to be the best block-matching technique, whereas the multiresolution Horn-Schunck technique was the best gradient optical flow method. The extracted thermal change during in vivo revascularization therapy is promising. In addition, we present an evaluation of several block-matching and optical flow motion estimation techniques.

Electrocardiography is the method of choice for cardiac electrophysiological evaluation. Arrhythmia is one of the most crucial problems in cardiology. So far, many methods have been developed for arrhythmia detection, recognition and classification. A popular method is ECG modeling using a basis function (such as wavelet, hermite or RBF) and classifying the coefficients of the basis functions. We present a new method based on non-uniform sampling (selecting 7 samples) of ECG signal. It is shown that Left and Right Bundle Branch block arrhythmia as well as normal signals can be better analyzed using a newly introduced method called Finite Rate of Innovation (FRI) and other types of arrhythmia can be better analyzed based on spline modeling. Therefore, a multi-stage algorithm is proposed for diagnosing and compression of ECG signal which is faster and yet accurate.

Growing tendency toward utilization of Laser and RF knives has opened a new port for thermal control applications in which ultrasound thermal detection is crucial. Ultrasound velocity is dependent on the thermal properties of the environment. In this paper we focus on tissue temperature detection using multiresolution steerable filter-based motion estimation. The proposed technique was evaluated on simulated and real in-vivo cases during surgical occlusion and reopening of renal segmental artery and demonstrated promising results for observation of internal organ temperature changes using only digital ultrasound systems for diagnosis and therapy. It is proved that being oriented in space and time, steerable filters can achieve more accurate results. Performing thermal detection methods on synthetic phantoms demonstrated good correlation between speckle shifts and the ground truth temperature. For the simulated images average thermal error was 0.68 degrees Celsius with a standard deviation of 0.79.

A two-dimensional temperature estimation method has been proposed based on the detection of shifts in speckle pattern location of ultrasound B-Mode digital images from a region of tissue undergoing thermal therapy. The speckle pattern shifts were due to the local temperature dependence of sound speed and thermal expansion in the heated region. Here in this paper we made use of optical-flow in order to achieve a better accuracy and lower computational burden. The accuracy of measurement of the temperature has been tested on simulated images and it is experimentally validated using tissue mimicking phantom. Good agreement was obtained from the simulated sequences (mean difference=0.1 and pick error was 0.6). The proposed method was found computationally faster compared to our previous work which was based on the cross correlation algorithm.

Since myocardial motion is directly related to cardiac vascular supply, it can be helpful in diagnosing the heart abnormalities. The most comprehensive and available imaging study of the cardiac function is B-Mode echocardiography. However diagnostic systems are expert dependent and motion is not clear in the B-mode echocardiography images and therefore many efforts are pointed toward proposing new methods to measure the motion accurately. So far there have been many methods for myocardial motion estimation such as affine registration, elastic registration or optical flow but each method suffers from lack of accuracy. To increase the accuracy of motion detection techniques, we propose a new algorithm based on a variational technique to combine the efficiencies of optical flow methods and affine registration in combination with multi-resolution spatiotemporal Spline moments. The evaluation was performed on simulated, synthetic and real data. A comparison between the proposed method and several other methods shows its better performance to measure the motion more accurately in the presence of shear, rotation and noise. The proposed method achieved rotational error of 2.6 degrees per frame and amplitude error of 3.7 percent per frame. These results demonstrate a better efficiency with respect to other B-Mode echocardiography motion estimation techniques such as Lucas-Kanade, Horn-Schunck and spatiotemporal affine technique.

An electrocardiogram (ECG) feature extraction and classification system has been developed and evaluated using Quartus II 7.1 belong to Altera Ltd. In wavelet domain QRS complexes were detected and each complex was used to locate the peaks of the individual waves. Then, fuzzy classifier block used these features to classify ECG beats. Three types of arrhythmias and abnormalities were detected using the procedure. The completed algorithm was embedded into Field Programmable Gate Array (FPGA). The completed prototype was tested through software-generated signals, in which test scenarios covering several kinds of ECG signals on MIT-BIH Database. For the purpose of feeding signals into the FPGA, a software was designed to read signal files and import them to the LPT port of computer that was connected to FPGA. From the results, it was achieved that the proposed prototype could do real time monitoring of ECG signal for arrhythmia detection. We also implemented algorithm in a sequential structure device like AVR microcontroller with 16 MHZ clock for the same purpose. External clock of FPGA is 50 MHZ and by utilizing of Phase Lock Loop (PLL) component inside device, it was possible to increase the clock up to 1.2 GHZ in internal blocks. Final results compare speed and cost of resource usage in both devices. It shows that in cost of more resource usage, FPGA provides higher speed of computation; because FPGA makes the algorithm able to compute most parts in parallel manner.