Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (40)
  • Open Access


    Segmentation of Cervical Cancer by OLHT Based DT-CWT Techniques

    P. R. Sheebha Rani1,*, R. Jemila Rose2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1579-1592, 2022, DOI:10.32604/iasc.2022.023587

    Abstract Every year, cervical cancer (CC) is the leading cause of death in women around the world. If detected early enough, this cancer can be treated, and patients will receive adequate care. This study introduces a novel ultrasound-based method for detecting CC. The Oriented Local Histogram Technique (OLHT) is used to improve the image corners in the cervical image (CI), and the Dual-Tree Complex Wavelet Transform (DT-CWT) is used to build a multi-resolution image (CI). Wavelet, and Local Binary Pattern are among the elements retrieved from this improved multi-resolution CI (LBP). The retrieved appearance is trained and tested using a feed-forward… More >

  • Open Access


    Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images

    Ayman M. Abdalla1,*, Mohammad Abu Awad2, Omar AlZoubi2, La'aly A. Al-Samrraie3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 797-814, 2022, DOI:10.32604/cmc.2022.024913

    Abstract The enlarged veins in the pampiniform venous plexus, known as varicocele disease, are typically identified using ultrasound scans. The medical diagnosis of varicocele is based on examinations made in three positions taken to the right and left testicles of the male patient. The proposed system is designed to determine whether a patient is affected. Varicocele is more frequent on the left side of the scrotum than on the right and physicians commonly depend on the supine position more than other positions. Therefore, the experimental results of this study focused on images taken in the supine position of the left testicles… More >

  • Open Access


    Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study

    Chichao Zheng, Yazhong Wang, Yadan Wang*, Qing He, Hu Peng

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 397-413, 2022, DOI:10.32604/cmes.2022.016308

    Abstract Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms were applied in VS imaging. In this paper, we proposed an adjustable generalized coherence factor (aGCF) for the synthetic aperture sequential beamforming (SASB) of VS imaging to improve image quality. The value of aGCF is adjusted by a sequence intensity factor (SIF) that is defined as the ratio between the effective low resolution scan lines (LRLs) intensity and total… More >

  • Open Access


    Lactoferrin-Conjugated Polylactic Acid Nanobubbles Encapsulated Perfluoropentane as a Contrast Agent for Ultrasound/Magnetic Resonance Dual-Modality Imaging

    Liqiong Ding1, Pingsheng Li2, Liu He1, Fengnan Xu1, Jieqiong Ding3,*, Binhua Luo1,*

    Journal of Renewable Materials, Vol.10, No.3, pp. 767-780, 2022, DOI:10.32604/jrm.2022.016903

    Abstract The development of contrast agents that can be activated by multiple modes is of great significance for tumor diagnosis. In this study, the lactoferrin (Lf)-conjugated polylactic acid (PLLA) nanobubbles (Lf-PLLA NBs) were used to encapsulate liquid perfluoropentane (PFP) with the double emulsion method, creating PFP loaded (PFP/Lf-PLLA) NBs for the ultrasound/magnetic resonance dual-modality imaging of subcutaneous tumor. The particle diameter and stability of nanobubbles were investigated by photon correlation spectroscopy. The biocompatibility of nanobubbles was preliminarily evaluated by cell proliferation and migration assay, hemolysis rate, and blood biochemistry analysis. A B-mode clinical ultrasound real-time imaging system was used to perform… More >

  • Open Access


    Adversarial Neural Network Classifiers for COVID-19 Diagnosis in Ultrasound Images

    Mohamed Esmail Karar1,2, Marwa Ahmed Shouman3, Claire Chalopin4,*

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

    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 auxiliary classifier. Each one includes… More >

  • Open Access


    Deep Learning Applications for COVID-19 Analysis: A State-of-the-Art Survey

    Wenqian Li1, Xing Deng1,2,*, Haijian Shao1, Xia Wang3

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

    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 absence of a vaccine, the… More > Graphic Abstract

    Deep Learning Applications for COVID-19 Analysis: A <i>State-of-the-Art</i> Survey

  • Open Access


    Implementing Delay Multiply and Sum Beamformer on a Hybrid CPU-GPU Platform for Medical Ultrasound Imaging Using OpenMP and CUDA

    Ke Song1,*, Paul Liu2, Dongquan Liu3

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

    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 Processing Units (CPUs). Consequently, we… More >

  • Open Access


    Lightweight Transfer Learning Models for Ultrasound-Guided Classification of COVID-19 Patients

    Mohamed Esmail Karar1,2, Omar Reyad1,3, Mohammed Abd-Elnaby4, Abdel-Haleem Abdel-Aty5,6, Marwa Ahmed Shouman7,*

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

    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 models, namely MobileNets, ShuffleNets, MENet… More >

  • Open Access


    The Research of Automatic Classification of Ultrasound Thyroid Nodules

    Yanling An1, Shaohai Hu1,*, Shuaiqi Liu2,3, Jie Zhao2,3,*, Yu-Dong Zhang4

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 203-222, 2021, DOI:10.32604/cmes.2021.015159

    Abstract This paper proposes a computer-aided diagnosis system which can automatically detect thyroid nodules (TNs) and discriminate them as benign or malignant. The system firstly uses variational level set active contour with gradients and phase information to complete automatic extraction of the boundaries of thyroid nodules images. Then according to thyroid ultrasound images and clinical diagnostic criteria, a new feature extraction method based on the fusion of shape, gray and texture is explored. Due to the imbalance of thyroid sample classes, this paper introduces a weight factor to improve support vector machine, offering different classes of samples with different weights. Finally,… More >

  • Open Access


    L’exploration axillaire en pratique quotidienne dans le parcours diagnostique d’un cancer du sein
    Axillary staging in daily practice in the diagnosis of breast cancer

    J. Boudier, G. Oldrini, C. Barlier, A. Lesur

    Oncologie, Vol.21, No.1, pp. 11-16, 2019, DOI:10.3166/onco-2019-0034

    Abstract When a breast cancer is diagnosed, the quality of the evaluation before treatment is essential to guide the therapeutic decision. The staging axillary is necessary because it estimates the regional extension of the disease, which makes it a paramount prognosis factor. Some different preoperative medical imaging can reveal metastasis axillary nodes. However, the axillary ultrasound remains the reference imaging and it also leads the biopsies too. Since theACOSOG-Z0011 trial, we are facing a therapeutic deescalation in the axillary surgery. According to recent results, we can note that the position of the axillary imaging is more and more important. The purpose… More >

Displaying 11-20 on page 2 of 40. Per Page