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  • Open Access

    ARTICLE

    Pre-Trained Deep Neural Network-Based Computer-Aided Breast Tumor Diagnosis Using ROI Structures

    Venkata Sunil Srikanth*, S. Krithiga

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 63-78, 2023, DOI:10.32604/iasc.2023.023474

    Abstract Deep neural network (DNN) based computer-aided breast tumor diagnosis (CABTD) method plays a vital role in the early detection and diagnosis of breast tumors. However, a Brightness mode (B-mode) ultrasound image derives training feature samples that make closer isolation toward the infection part. Hence, it is expensive due to a meta-heuristic search of features occupying the global region of interest (ROI) structures of input images. Thus, it may lead to the high computational complexity of the pre-trained DNN-based CABTD method. This paper proposes a novel ensemble pre-trained DNN-based CABTD method using global- and local-ROI-structures of B-mode ultrasound images. It conveys… More >

  • Open Access

    ARTICLE

    Extended Speckle Reduction Anisotropic Diffusion Filter to Despeckle Ultrasound Images

    P. L. Joseph Raj, K. Kalimuthu*, Sabitha Gauni, C. T. Manimegalai

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1187-1196, 2022, DOI:10.32604/iasc.2022.026052

    Abstract Speckle Reduction Anisotropic Diffusion filter which is used to despeckle ultrasound images, perform well at homogeneous region than in heterogeneous region resulting in loss of information available at the edges. Extended SRAD filter does the same, preserving better the edges in addition, compared to the existing SRAD filter. The proposed Extended SRAD filter includes the intensity of four more neighboring pixels in addition with other four that is meant for SRAD filter operation. So, a total of eight pixels are involved in determining the intensity of a single pixel. This improves despeckling performance by maintaining the information accessible at an… More >

  • Open Access

    ARTICLE

    Combined Echocardiography and Lung Ultrasound for Extubation Outcome Prediction in Children after Cardiac Surgery

    Muzi Li1,4, Hong Meng1,4,*, Liang Zhang2, Yuzi Zhou3, Chao Liang4, Zhiling Luo4, Hao Wang1,*

    Congenital Heart Disease, Vol.17, No.3, pp. 231-244, 2022, DOI:10.32604/chd.2022.019480

    Abstract Background: Children are at risk of extubation failure after congenital heart disease surgery. Such cases should be identified to avoid possible adverse consequences of failed extubation. This study aimed to identify ultrasound predictors of successful extubation in children who underwent cardiac surgery. Methods: Children aged 3 months to 6 years who underwent cardiac surgery (if they were intubated for >6 h and underwent a spontaneous breathing trial) were included in this study. Results: We included 83 children who underwent surgery for congenital heart disease. Transthoracic echocardiography and lung ultrasound were performed immediately before spontaneous breathing trials. Upon spontaneous breathing trial… More >

  • Open Access

    ARTICLE

    A High-Efficiency Inversion Method for the Material Parameters of an Alberich-Type Sound Absorption Coating Based on a Deep Learning Model

    Yiping Sun1,2, Jiadui Chen1, Qiang Bai1, Xuefeng Zhao1, Meng Tao1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1693-1716, 2022, DOI:10.32604/cmes.2022.019336

    Abstract Research on the acoustic performance of an anechoic coating composed of cavities in a viscoelastic material has recently become an area of great interest. Traditional forward research methods are unable to manipulate sound waves accurately and effectively, are difficult to analyse, have time-consuming solution processes, and have large optimization search spaces. To address these issues, this paper proposes a deep learning-based inverse research method to efficiently invert the material parameters of Alberich-type sound absorption coatings and rapidly predict their acoustic performance. First, an autoencoder (AE) model is pretrained to reconstruct the viscoelastic material parameters of an Alberich-type sound absorption coating,… More >

  • Open Access

    ARTICLE

    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

    ARTICLE

    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

    ARTICLE

    A Complete Analysis of Clarity (C50) Using I-SIMPA to Maintain Ideal Conditions in an Acoustic Chamber

    R. Adithya Pillai1, S. Sakthivel Murugan2,*, Guruprasad Gupta1

    Sound & Vibration, Vol.56, No.1, pp. 51-64, 2022, DOI:10.32604/sv.2022.012085

    Abstract In any closed environment considered, it can be seen that the acoustic parameters are inherently not constant over the entire area considered. In a closed environment, it is ideally preferred to maintain the acoustic parameters as constant so that there exists better quality of sound leading to better auditory perception with respect to the audience. Practically, some of the acoustic parameters like reverberation time and clarity do not strictly pertain to the pattern obtained theoretically. In this paper, simulations are carried out using I-SIMPA under different values of Sound Transmission Class (STC), source position, distribution and the chamber dimensions and… More >

  • Open Access

    ARTICLE

    Optimization of Sound Absorption and Insulation Performances of a Dual-Cavity Resonant Micro-Perforated Plate

    Wei Chen1,2, Zhaofeng Guo3,4,*, Hongda Feng3,4, Sheng Hu1,2, Ling Lu1,2, Chuanmin Chen3,4, Xiaowen Wu1,2, Hao Cao1,2

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.2, pp. 481-496, 2022, DOI:10.32604/fdmp.2022.015746

    Abstract This study investigates a dual-cavity resonant composite sound-absorbing structure based on a micro-perforated plate. Using the COMSOL impedance tube model, the effects of various structural parameters on sound absorption and sound insulation performances are analyzed. Results show that the aperture of the micro-perforated plate has the greatest influence on the sound absorption coefficient; the smaller the aperture, the greater is this coefficient. The thickness of the resonance plate has the most significant influence on the sound insulation and resonance frequency; the greater the thickness, the wider the frequency domain in which sound insulation is obtained. In addition, the effect of… More >

  • Open Access

    ARTICLE

    Classification of Elephant Sounds Using Parallel Convolutional Neural Network

    T. Thomas Leonid1,*, R. Jayaparvathy2

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1415-1426, 2022, DOI:10.32604/iasc.2022.021939

    Abstract Human-elephant conflict is the most common problem across elephant habitat Zones across the world. Human elephant conflict (HEC) is due to the migration of elephants from their living habitat to the residential areas of humans in search of water and food. One of the important techniques used to track the movements of elephants is based on the detection of Elephant Voice. Our previous work [] on Elephant Voice Detection to avoid HEC was based on Feature set Extraction using Support Vector Machine (SVM). This research article is an improved continuum of the previous method using Deep learning techniques. The current… More >

  • Open Access

    ARTICLE

    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 >

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