Developing an automatic brachial artery segmentation and bloodstream analysis tool using possibilistic C-means clustering from color doppler ultrasound images

Automatic segmentation of brachial artery and blood-flow dynamics are important for early detection of cardiovascular disease and other vascular endothelial malfunctions. In this paper, we propose a software that is noise tolerant and fully automatic in segmentation of brachial artery from color Doppler ultrasound images. Possibilistic C-Means clustering algorithm is applied to make the automatic segmentation. We use HSV color model to enhance the contrast of bloodstream area in the input image. Our software also provides index of hemoglobin distribution with respect to the blood flow velocity for pathologists to proceed further analysis. In experiment, the proposed method successfully extracts the target area in 59 out of 60 cases (98.3%) with field expert’s verification

Automatic Segmentation of Brachial Artery based on Fuzzy C-Means Pixel Clustering from Ultrasound Images

Automatic extraction of brachial artery and measuring associated indices such as flow-mediated dilatation and Intima-media thickness are important for early detection of cardiovascular disease and other vascular endothelial malfunctions. In this paper, we propose the basic but important component of such decision-assisting medical software development – noise tolerant fully automatic segmentation of brachial artery from ultrasound images. Pixel clustering with Fuzzy C-Means algorithm in the quantization process is the key component of that segmentation with various image processing algorithms involved. This algorithm could be an alternative choice of segmentation process that can replace speckle noise-suffering edge detection procedures in this application domain

Comparison of safety and efficacy between therapeutic or intermediate versus prophylactic anticoagulation for thrombosis in COVID-19 patients: a systematic review and meta-analysis

Background Patients with coronavirus disease 2019 (COVID-19) infections often have macrovascular or microvascular thrombosis and inflammation, which are known to be associated with a poor prognosis. Heparin has been hypothesized that administration of heparin with treatment dose rather than prophylactic dose for prevention of deep vein thrombosis in COVID-19 patients. Methods Studies comparing therapeutic or intermediate anticoagulation with prophylactic anticoagulation in COVID-19 patients were eligible. Mortality, thromboembolic events, and bleeding were the primary outcomes. PubMed, Embase, the Cochrane Library, and KMbase were searched up to July 2021. A meta-analysis was performed using random-effect model. Subgroup analysis was conducted according to disease severity. Results Six randomized controlled trials (RCTs) with 4,678 patients and four cohort studies with 1,080 patients were included in this review. In the RCTs, the therapeutic or intermediate anticoagulation was associated with significant reductions in the occurrence of thromboembolic events (5 studies, n=4,664; relative risk [RR], 0.72; P=0.01), and a significant increase in bleeding events (5 studies, n=4,667; RR, 1.88; P=0.004). In the moderate patients, therapeutic or intermediate anticoagulation was more beneficial than prophylactic anticoagulation in terms of thromboembolic events, but showed significantly higher bleeding events. In the severe patients, the incidence of thromboembolic and bleeding events in the therapeutic or intermediate. Conclusions The study findings suggest that prophylactic anticoagulant treatment should be used in patients with moderate and severe COVID-19 infection groups. Further studies are needed to determine more individualized anticoagulation guidance for all COVID-19 patients

Comparison of the formula accuracy for calculating multifocal intraocular lens power: a single center retrospective study in Korean patients

Abstract This study evaluated the accuracy of newer formulas (Barrett Universal II, EVO 2.0, Kane, Hoffer QST, and PEARL-DGS) and the Haigis formula in Korean patients with the Alcon TFNT multifocal intraocular lens. In total, 3100 randomly selected eyes of 3100 patients were retrospectively reviewed. After constant optimization, the standard deviation (SD) of the prediction error was assessed for the entire group, and the root mean square error was compared for short and long axial length (AL) subgroup analysis. The Cooke-modified AL (CMAL) was experimentally applied to the Haigis formula. All the newer formulas performed well, but they did not significantly outperform the Haigis formula. In addition, all the newer formulas exhibited significant myopic outcomes (− 0.23 to − 0.29 diopters) in long eyes. Application of the CMAL to the Haigis formula with single constant optimization produced similar behavior and higher correlation with the newer formulas. The CMAL-applied triple-optimized Haigis formula yielded a substantially smaller SD, even superior to the Barrett and Hoffer QST formulas. The AL modification algorithms such as the CMAL used in newer formulas to cope with optical biometry’s overestimation of the AL in long eyes seemed to overcompensate, particularly in the long eyes of the East Asian population

Impact of Deep-Learning Based Reconstruction on Single-Breath-Hold, Single-Shot Fast Spin-Echo in MR Enterography for Crohn’s Disease

Purpose To assess the quality of four images obtained using single-breath-hold (SBH), single-shot fast spin-echo (SSFSE) and multiple-breath-hold (MBH) SSFSE with and without deep-learning based reconstruction (DLR) in patients with Crohn’s disease. Materials and Methods This study included 61 patients who underwent MR enterography (MRE) for Crohn’s disease. The following images were compared: SBH-SSFSE with (SBH-DLR) and without (SBHconventional reconstruction [CR]) DLR and MBH-SSFSE with (MBH-DLR) and without (MBH-CR) DLR. Two radiologists independently reviewed the overall image quality, artifacts, sharpness, and motionrelated signal loss using a 5-point scale. Three inflammatory parameters were evaluated in the ileum, the terminal ileum, and the colon. Moreover, the presence of a spatial misalignment was evaluated. Signal-to-noise ratio (SNR) was calculated at two locations for each sequence. Results DLR significantly improved the image quality, artifacts, and sharpness of the SBH images. No significant differences in scores between MBH-CR and SBH-DLR were detected. SBH-DLR had the highest SNR (p < 0.001). The inter-reader agreement for inflammatory parameters was good to excellent (κ = 0.76–0.95) and the inter-sequence agreement was nearly perfect (κ = 0.92–0.94). Misalignment artifacts were observed more frequently in the MBH images than in the SBH images (p < 0.001). Conclusion SBH-DLR demonstrated equivalent quality and performance compared to MBH-CR. Furthermore, it can be acquired in less than half the time, without multiple BHs and reduce slice misalignments

Built-in Fault Diagnosis for Tunable Analog Systems Using an Ensemble Method

This paper presents a new low-cost fault diagnosis technique based on Built-in Self Test (BIST). The method enables rapid and accurate identification of weak spots in a design and potential problems in the manufacturing process, thereby leading to a significant reduction in time-tomarket. Fault diagnosis is accelerated with available onchip BIST which can generate low-cost signatures (performance parameters). Imperfect signatures due to limited onchip resources and accuracy are compensated in two ways. Supplemental signatures are obtained from a re-configured Device Under Test (DUT) by parameter tuning, leading to improvements in diagnosability. Secondly, diagnosis accuracy is significantly improved by using an ensemble method which has been widely used in data mining. The technique can be used to identify single as well as multiple faults, and can also be used to facilitate a self-repair mechanism by accurately identifying the source of errors. Simulation results are presented to validate the technique.

A Tunable Foreground Self-Calibration Scheme for Split Successive-Approximation Register Analog-to-Digital Converter

The capacitor mismatch among diverse defects caused by variations in the manufacturing process significantly affects the linearity of the capacitor array used to implement the capacitive digital-to-analog converter (CDAC) in the successive-approximation register (SAR) analog-to-digital converter (ADC). Accordingly, the linearity of the SAR ADC is limited by that of capacitor array, resulting in serious yield loss. This paper proposes an efficient foreground self-calibration technique to enhance the linearity of the SAR ADCs by mitigating the capacitor mismatch based on the split ADC architecture along with variable capacitors. In this work, two ADC channels (i.e., ADC1 and ADC2) for the split ADC architecture include their capacitive DACs (CDACs) whose binary-weighted capacitor arrays consist of variable capacitors. A charge-sharing SAR ADC is used for each ADC channel. In the normal operation mode, their digital outputs are averaged to be the final ADC output, as in a conventional split ADC. In the calibration mode, every single binary-weighted capacitor for the two ADCs is sequentially calibrated by making parallel or/and antiparallel connection among two or thee capacitors from the two channels. For instance, because the capacitors of the CDACs ideally exhibit the binary-weighted relation as Cn=2×Cn−1, the variable capacitor Cn of ADC1 can be updated to be closest to the sum of Cn−1 of ADC1 and Cn−1 of ADC2 for the calibration. For the process, the two capacitor arrays of the two ADCs can be reconfigured to be connected to each other, so that the Cn of ADC1 can be connected with two of the Cn−1 of ADC1 and ADC2 in antiparallel. The two voltages at the top and the bottom plates of the CDAC are compared by a comparator of ADC1, and the comparison results are used to update Cn. This process is iterated, until Cn is in agreement with the sum of two of Cn−1. Finally, all the capacitors can be calibrated in this way to have the binary-weighted relation. The simulation results based on the proposed work with a split SAR ADC model verified that the proposed technique can be practically used, by showing that the total harmonic distortion and the signal-to-noise-and-distortion ratio were enhanced by 21.8 dB and 6.4 dB, respectively