Use of Ultrasound to Observe Mycosis Fungoides: A Case Report and Review of Literature

Background: Mycosis fungoides (MF) is the most common form of cutaneous T-cell lymphoma with many clinicopathological variants, thus difficult to diagnose in its early stages. Case Presentation: This case report is about a 76 years old Chinese woman presented with 2 years history of erythematous plaque on the lateral right thigh, after combining clinical manifestations with results of pathological examinations, it is consistent with the diagnosis of MF. Discussion: Mycosis fungoides (MF) is the most common form of cutaneous T-cell lymphoma. Patient in this case had a long course of disease and repeated attacks. Ultrasound shows small patch of liquid dark area of the lesion. Color Doppler image shows rich blood flow which just looks like lacustrine. Thick and nourishing blood vessels could be seen in the depth. Conclusion: Our case report using ultrasound to observe MF and demonstrate that ultrasound is helpful in diagnosing and evaluating effectiveness in treating MF.

A Micro-flow Phantom for Superficial Micro-vasculature Imaging

Visualization of cutaneous micro-vasculatures is a powerful approach assisting in the diagnosis of skin vascular disorders. These minute structures can be visualized by high-frequency ultrasound (HFUS) using ultrafast Doppler imaging. Ultrasound flow phantoms have been used as assessment tools to evaluate the performance of the ultrasound imaging system, however, to optimize the imaging system for visualization of micro-structures, flow phantom with micro-channels is required which are usually difficult to fabricate. Here, we design a simple approach for micro-flow phantom which is easy to fabricate and cast for detection of micro-circulation in superficial micro-structures. The proposed approach features (i) the micro-channels of 200-micron at the depth of 4 mm (ii) casted in the cryogel mixture of Poly-vinyl alcohol (PVA) and (iii) infused at flow speed of 30 mm/s using infusion pump. Visualization of micro-flow channel in power Doppler image obtained by HFUS ultrafast Doppler imaging reveals that the proposed micro-flow phantom could serve as a viable assessment tool for optimizing the system for in-vivo cutaneous micro-vasculature imaging.

Classification of Drones Using Edge-Enhanced Micro-Doppler Image Based on CNN

The development of advanced radar system for detection and classification of UAVs is an essential requirement for today’s societal security. Such intelligent system could able to analyze the received radar signal and extract relevant information by utilizing sophisticated algorithm. In this letter, the utilization of micro-Doppler signature (MDS) for classification of drones, using convolutional neural network (CNN) model has been presented. We have generated images of micro-Doppler signatures using W-band radar system and used it for classification purpose. In this work, phase stretch transform (PST) has been utilized for edge detection and enhancement of the micro-Doppler images, to generate the edge-enhanced micro-Doppler image (EMDI). The comparison based on classification performance of CNN with different input datasets shows that the EMDI based CNN model outperformed the micro-Doppler image (MDI) based model.

Modeling of range-Doppler images of multicopters, formed by radar with continuous frequency-modulated signal.

The paper presents an approach to modeling of a range-Doppler image of a multicopter, formed in a radar with a wide-band continuous signal. A feature of the approach is taking into account the observation angle, spatial orientation and the current angle of rotation of each of the multicopter propellers, based on wide-band all-angle estimates of their complex-valued reflection coefficients on horizontally and vertically polarized signals, formed using the microwave devices CAE system. The results of simulation of the range-Doppler image of the DJI Phantom 4 multicopter propeller system based on the actual recording of its flight parameters loggeded with the onboard autopilot are presented. Using the proposed model it was defined that the feature of range-Doppler images formed with wide-band continuous radar is the components frequency shifting not only on the Doppler frequency coordinate, but the slant detection range coordinate too.

Prenatal diagnosis of Shone’s syndrome: ultrasonographic features and differential diagnosis with coarctation of the aorta

Objective：To improve the prenatal diagnosis of Shone’s syndrome and identify the mitral valve obstruction associated with the anomaly by comparing the fetal echocardiographic features between Shone’s syndrome and coarctation of the aorta (CoA). Method: Between January 2015 to December 2019, 17 fetuses were diagnosed with Shone’s syndrome prenatally and 8 were analyzed in our final study, their data were compared to normal controls and CoA cases. The main points of identification were summarized. Results: By comparing data between three groups, elevated PA/AO ratio and RV/LV ratio were detected in both Shone’s syndrome and CoA cases. However, TVC/MVC ratios was only increased in Shone’s syndrome. Analysis revealed that the TVC/MVC ratio had the best capability in predicting Shone’s syndrome. Ultrasonographic features of mitral valve obstruction in Shone’s syndrome were unique which help clinicians to distinguish the anomaly from CoA, including (1) morphologic changes in short-axis view: restrictive opening of the mitral valve with diastolic deformity, thickened leaflets, echo-enhancement of chordae tendineae and mitral valve, single papillary muscle or dominant papillary muscle; (5) in color Doppler image: decreased antegrade flow and abnormal flow pattern of mitral valve. Conclusion: There are two key points of prenatal diagnosis of Shone’s syndrome which could help fetal cardiologist to distinguish Shone’s syndrome from CoA in clinical practice, including (1) echocardiographic measurements: the elevated TVC/MVC ratio; (2) morphologic changes of mitral valve indicating left ventricle inflow obstruction in two-dimension short-axis section view.

Influence of Average Annual Mean Serum Ferritin Levels on Left Ventricular Function in Patients With β Thalassemia

Cardiac complications are the most important cause of mortality and morbidity in Beta-Thalassemia Major (B-TM). The aim of our study was to determine the influence of Average Annual Mean Serum Ferritin (AAMSF) levels on cardiac function in patients suffering from B-TM. In this cross-sectional study, 50 patients of 5-15 years with B-TM were enrolled in the absence of clinical signs and symptoms of cardiac dysfunction. Left ventricular function was studied by using tissue Doppler image (TDI), pulse wave Doppler (PWD). AAMSF level was measured for 12 months. Patient groups were subdivided into two groups, group A with AAMSF level below 1000 ng/ml and group with B with AAMSF level above 1000 ng/ml. The Case group included 24(48%) males and 26(52%) females which were compared with 50 healthy subjects composed of 27(54%) males and 23 (46%) females (control group). The AAMSF Levels were 1054.60±687.95 ng/ml. By using PDW, in patients with AAMSF below 1000 ng/ml, The Parameters of the E, A, E/A E-DT had no significant difference with health groups (P=0.808, P=0.820, P=0.231 and P=0.061, respectively). No significant difference was revealed in parameters of E’, IVCT and ET in patients with AAMSF below 1000 ng/ml by using TDI in comparison to control (P=0.155, P=0.683, P=0.222, respectively).however, other TDI indexes including A’, E’/A’, IVRT, S,’ LVMPI, E/E’ had a significant difference with health group (P=0.014, P=0.041, P=0.045, P=0.002, P=0.021, and P=0.002, respectively). At patients with above AAMSF 1000 ng/mL, both PDW and TDI parameters had significant differences with the health group. There was no correlation among AAMSF levels and PWD or TDI indexes. The evidence from this study suggests that subclinical systolic and diastolic LV dysfunction has happened with AAMSF level above 1000 ng/ml, and according to our result, TDI is found more useful than PWD for subclinical cardiac evaluation.

Applying Color Doppler Image based Virtual Surgery in Placenta Previa Cesarean Section

Objective: To study the application of image processing technology in cesarean section of placenta previa, thereby reducing the occurrence of high-risk pregnancy. Methods: First, the method of gray image enhancement is analyzed. This method enhances the gray difference between the target and the background, highlights useful information, summarizes the source and type of noise, and proposes common filtering and noise reduction methods to suppress the noise. For edge detection, pixel-level edge detection operators and sub-pixel-level edge detection operators are summarized. The Canny edge detection operator and the Gaussian fitting sub-pixel edge detection operator are introduced in detail, and innovative improvements are carried out for resolving the deficiencies of the algorithm. Results: The improved adaptive iterative segmentation thresholding method results in a threshold of T = 98 and 11 iterations. The image segmentation quality of the improved Otsu method has been greatly enhanced. After the second segmentation, the improved Otsu method finds the optimal threshold T = 76. Conclusion: Color Doppler ultrasound image processing technology has excellent application in placenta previa cesarean section.

Hybrid SVM-CNN Classification Technique for Human–Vehicle Targets in an Automotive LFMCW Radar

Human–vehicle classification is an essential component to avoiding accidents in autonomous driving. The classification technique based on the automotive radar sensor has been paid more attention by related researchers, owing to its robustness to low-light conditions and severe weather. In the paper, we propose a hybrid support vector machine–convolutional neural network (SVM-CNN) approach to address the class-imbalance classification of vehicles and pedestrians with limited experimental radar data available. A two-stage scheme with the combination of feature-based SVM technique and deep learning-based CNN is employed. In the first stage, the modified SVM technique based on these distinct physical features is firstly used to recognize vehicles to effectively alleviate the imbalance ratio of vehicles to pedestrians in the data level. Then, the residual unclassified images will be used as inputs to the deep network for the subsequent classification, and we introduce a weighted false error function into deep network architectures to enhance the class-imbalance classification performance at the algorithm level. The proposed SVM-CNN approach takes full advantage of both the locations of underlying class in the entire Range-Doppler image and automatical local feature learning in the CNN with sliding filter bank to improve the classification performance. Experimental results demonstrate the superior performances of the proposed method with the F 1 score of 0.90 and area under the curve (AUC) of the receiver operating characteristic (ROC) of 0.99 over several state-of-the-art methods with limited experimental radar data available in a 77 GHz automotive radar.

Prenatal Diagnosis of Shone’s Syndrome by Fetal Echocardiography

Background：Shone’s syndrome is a rare complex with few data published on its prenatal diagnosis, this study aimed to compare the fetal echocardiographic features between Shone’s syndrome fetuses and coarctation of the aorta (CoA) fetuses to improve the prenatal diagnosis of Shone’s syndrome and identify the mitral valve obstruction associated with the anomaly. Methods: Retrospective study was performed. Between January 2015 to December 2019, fourteen fetuses diagnosed with Shone’s syndrome were enrolled and ten were analyzed in our final study, their clinical information and echocardiographic features were compared to normal controls (N=30) and CoA cases (N=10). The main points of identification were summarized. Results: Comparing to normal controls, the PA/AO ratio was increased in both Shone’s syndrome and CoA, but Shone’s syndrome fetuses had higher PA/AO ratio than CoA fetuses (P=0.006). RV/LV and TVC/MVC ratios were only elevated in Shone’s syndrome cases (P<0.0001, P<0.0001). Analysis revealed that the TVC/MVC ratio had the best capability in predicting Shone’s syndrome and fetuses with TVC/MVC ratio over 1.290 were more likely to have Shone’s syndrome rather than CoA. Meanwhile, the main points of identification in mitral valve obstruction included (1) restrictive opening of the mitral valve, thickened leaflets, echo-enhancement of chordae tendineae and single papillary muscle in short-axis section view; (2) decreased antegrade flow and abnormal flow pattern of mitral valve in color Doppler image. Chi-square test revealed that restrictive opening of the mitral valve and single papillary muscle were the most relevant features of mitral valve obstruction. Conclusions: There are several parameters of prenatal diagnosis of Shone’s syndrome by fetal echocardiography, including (1) echocardiographic measurements: elevated RV/LV ratio, PA/AO ratio and TVC/MVC ratio, of these, the TVC/MVC ratio has the best capability in predicting Shone’s syndrome; (2) morphologic changes in short-axis section view: restrictive opening of the mitral valve and single papillary muscle are the most relevant features of Shone’s syndrome.