Mohamed Esmail Karar^1,2, Marwa Ahmed Shouman³, Claire Chalopin^4,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1683-1697, 2022, DOI:10.32604/cmc.2022.018564 - 07 September 2021

Abstract The novel Coronavirus disease 2019 (COVID-19) pandemic has begun in China and is still affecting thousands of patient lives worldwide daily. Although Chest X-ray and Computed Tomography are the gold standard medical imaging modalities for diagnosing potentially infected COVID-19 cases, applying Ultrasound (US) imaging technique to accomplish this crucial diagnosing task has attracted many physicians recently. In this article, we propose two modified deep learning classifiers to identify COVID-19 and pneumonia diseases in US images, based on generative adversarial neural networks (GANs). The proposed image classifiers are a semi-supervised GAN and a modified GAN with… More >

Steven J. Lomax¹, Daniela A. Haehn¹, Eric Robinson¹, Rachel Pung Page², Edsel Bittencourt³, Mark F.B. Hurdle³, Steven P. Petrou¹

Canadian Journal of Urology, Vol.28, No.4, pp. 10778-10782, 2021

Abstract Introduction: To compare the accuracy of the transcutaneous ultrasound (US) in detecting the tibial nerve (TN) as opposed to digital palpation in the performance of posterior tibial nerve stimulation (PTNS).
Materials and methods: After Institutional Review Board (IRB) approval, 25 adults were enrolled to quantify the difference in position of the distal TN by the use of US as opposed to cutaneous palpation. The position of the TN was determined first by the palpation method and then by using a L12-4MHz high frequency Linear Array Transducer. The difference in position between the two methods was determined in… More >

Andrew M. Fang¹, Zachary R. Burns¹, Alexander P. Nocera¹, Rex A. Cardan², Jeffrey W. Nix^1,3, Kristin K. Porter^4,*, Andrew M. McDonald^2,3,*, Soroush Rais-Bahrami^1,3,4

Canadian Journal of Urology, Vol.28, No.5, pp. 10817-10823, 2021

Abstract Introduction: We aim to investigate if the addition of MRI-US fusion biopsy (FB) can aid in radiation planning and alter the boost field in cases of stereotactic body radiation therapy (SBRT) for prostate cancer with a simultaneous integrated boost (SIB) to a magnetic resonance imaging (MRI)-defined intraprostatic lesion.
Materials and methods: Patients undergoing SBRT with SIB for biopsy-proven prostatic adenocarcinoma and a pre-radiation MRI were retrospectively reviewed. 36.25 Gy in 5 fractions was delivered to the entire prostate along with SIB of 40 Gy to an MRI-defined intraprostatic lesion. Demographic, radiation planning details, and post-procedural outcomes were… More >

Samuel Helrich¹, Wesley Pate¹, Nishant Garg¹, Philip Barbosa², Shaun Wason¹

Canadian Journal of Urology, Vol.28, No.6, pp. 10889-10899, 2021

Abstract Introduction: To compare pelvic ultrasound (PUS) and transrectal ultrasound (TRUS) to magnetic resonance imaging (MRI) in the estimation of prostate size.
Materials and methods: After IRB approval, we performed a single-center, retrospective study of 91 patients who had prostate sizing between August 2013 and June 2017. Correlation, reliability, and agreement between PUS, TRUS, and MRI were calculated through the Pearson coefficient, intraclass correlation coefficient, and Bland-Altman analysis, respectively. Data was stratified by prostate size, body mass index, and time between imaging acquisition.
Results: A total of 91 patients underwent all three imaging methods. Median age was 64, median… More >

Ali Askari¹, Ali Salehi Sahl Abadi^2,*, Alimardan Alinia³, Milad Pourjaafar⁴, Aref Honairi Haghighi⁵, Elham Akhlaghi Pirposhteh⁶

Sound & Vibration, Vol.55, No.4, pp. 329-341, 2021, DOI:10.32604/sv.2021.016662 - 18 October 2021

Abstract Among the harmful occupational factors, noise is the most common exposure in the oil industrial workplaces. The present study aimed to prioritize sound pollution areas in central processing facilities (CPF) of an oil field in order to provide corrective action in the studied industry and similar industries. After reviewing the issued permit to work, job description and noise dosimetry test, the evaluated areas were selected then sound pressure levels in the referenced areas investigated according to ISO 9612–2009 (E) next the noise map prepared for all selected areas. For identifying the prioritized areas to implement… More >

Wenqian Li¹, Xing Deng^1,2,*, Haijian Shao¹, Xia Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 65-98, 2021, DOI:10.32604/cmes.2021.016981 - 24 August 2021

Abstract The COVID-19 has resulted in catastrophic situation and the deaths of millions of people all over the world. In this paper, the predictions of epidemiological propagation models, such as SIR and SEIR, are introduced to analyze the earlier COVID-19 propagation. The deep learning methods combined with transfer learning are familiar with classification-detection approaches based on chest X-ray and CT images are presented in detail. Besides, deep learning approaches have also been applied to lung ultrasound (LUS), which has been shown to be more sensitive than chest X-ray and CT images in detecting COVID-19. In the… More > Graphic Abstract

Mohamed Esmail Karar^1,2, Omar Reyad^1,3,*, Abdel-Haleem Abdel-Aty⁴, Saud Owyed⁵, Mohd F. Hassan⁶

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4095-4111, 2021, DOI:10.32604/cmc.2021.019059 - 24 August 2021

Abstract Smart precision agriculture utilizes modern information and wireless communication technologies to achieve challenging agricultural processes. Therefore, Internet of Things (IoT) technology can be applied to monitor and detect harmful insect pests such as red palm weevils (RPWs) in the farms of date palm trees. In this paper, we propose a new IoT-based framework for early sound detection of RPWs using fine-tuned transfer learning classifier, namely InceptionResNet-V2. The sound sensors, namely TreeVibes devices are carefully mounted on each palm trunk to setup wireless sensor networks in the farm. Palm trees are labeled based on the sensor… More >

Ke Song^1,*, Paul Liu², Dongquan Liu³

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1133-1150, 2021, DOI:10.32604/cmes.2021.016008 - 11 August 2021

Abstract A novel beamforming algorithm named Delay Multiply and Sum (DMAS), which excels at enhancing the resolution and contrast of ultrasonic image, has recently been proposed. However, there are nested loops in this algorithm, so the calculation complexity is higher compared to the Delay and Sum (DAS) beamformer which is widely used in industry. Thus, we proposed a simple vector-based method to lower its complexity. The key point is to transform the nested loops into several vector operations, which can be efficiently implemented on many parallel platforms, such as Graphics Processing Units (GPUs), and multi-core Central… More >

Xiaoyan Zhao^1,*, Lin Zhou², Ying Tong¹, Yuxiao Qi¹, Jingang Shi³

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 361-371, 2021, DOI:10.32604/iasc.2021.018823 - 26 July 2021

Abstract In order to improve the performance of microphone array-based sound source localization (SSL), a robust SSL algorithm using convolutional neural network (CNN) is proposed in this paper. The Gammatone sub-band steered response power-phase transform (SRP-PHAT) spatial spectrum is adopted as the localization cue due to its feature correlation of consecutive sub-bands. Since CNN has the “weight sharing” characteristics and the advantage of processing tensor data, it is adopted to extract spatial location information from the localization cues. The Gammatone sub-band SRP-PHAT spatial spectrum are calculated through the microphone signals decomposed in frequency domain by Gammatone… More >

Mohamed Esmail Karar^1,2, Omar Reyad^1,3, Mohammed Abd-Elnaby⁴, Abdel-Haleem Abdel-Aty^5,6, Marwa Ahmed Shouman^7,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2295-2312, 2021, DOI:10.32604/cmc.2021.018671 - 21 July 2021

Abstract Lightweight deep convolutional neural networks (CNNs) present a good solution to achieve fast and accurate image-guided diagnostic procedures of COVID-19 patients. Recently, advantages of portable Ultrasound (US) imaging such as simplicity and safe procedures have attracted many radiologists for scanning suspected COVID-19 cases. In this paper, a new framework of lightweight deep learning classifiers, namely COVID-LWNet is proposed to identify COVID-19 and pneumonia abnormalities in US images. Compared to traditional deep learning models, lightweight CNNs showed significant performance of real-time vision applications by using mobile devices with limited hardware resources. Four main lightweight deep learning… More >