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  • Open Access


    A Novel Approach to Breast Tumor Detection: Enhanced Speckle Reduction and Hybrid Classification in Ultrasound Imaging

    K. Umapathi1,*, S. Shobana1, Anand Nayyar2, Judith Justin3, R. Vanithamani3, Miguel Villagómez Galindo4, Mushtaq Ahmad Ansari5, Hitesh Panchal6,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1875-1901, 2024, DOI:10.32604/cmc.2024.047961

    Abstract Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effective treatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breast cancer from ultrasound images. The primary challenge is accurately distinguishing between malignant and benign tumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentation and classification. The main objective of the research paper is to develop an advanced methodology for breast ultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, and machine learning-based classification. A unique approach… More >

  • Open Access


    A Transfer Learning Approach Based on Ultrasound Images for Liver Cancer Detection

    Murtada K. Elbashir1, Alshimaa Mahmoud2, Ayman Mohamed Mostafa1,*, Eslam Hamouda1, Meshrif Alruily1, Sadeem M. Alotaibi1, Hosameldeen Shabana3,4, Mohamed Ezz1,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5105-5121, 2023, DOI:10.32604/cmc.2023.037728

    Abstract The convolutional neural network (CNN) is one of the main algorithms that is applied to deep transfer learning for classifying two essential types of liver lesions; Hemangioma and hepatocellular carcinoma (HCC). Ultrasound images, which are commonly available and have low cost and low risk compared to computerized tomography (CT) scan images, will be used as input for the model. A total of 350 ultrasound images belonging to 59 patients are used. The number of images with HCC is 202 and 148, respectively. These images were collected from ultrasound cases.info (28 Hemangiomas patients and 11 HCC… More >

  • Open Access


    Speckle Noise Suppression in Ultrasound Images Using Modular Neural Networks

    G. Karthiha*, Dr. S. Allwin

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1753-1765, 2023, DOI:10.32604/iasc.2023.022631

    Abstract In spite of the advancement in computerized imaging, many image modalities produce images with commotion influencing both the visual quality and upsetting quantitative image analysis. In this way, the research in the zone of image denoising is very dynamic. Among an extraordinary assortment of image restoration and denoising techniques the neural network system-based noise suppression is a basic and productive methodology. In this paper, Bilateral Filter (BF) based Modular Neural Networks (MNN) has been utilized for speckle noise suppression in the ultrasound image. Initial step the BF filter is used to filter the input image.… More >

  • Open Access


    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… More >

  • Open Access


    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 More >

  • 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 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… 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… More >

  • Open Access


    Fully Automatic Segmentation of Gynaecological Abnormality Using a New Viola–Jones Model

    Ihsan Jasim Hussein1, M. A. Burhanuddin2, Mazin Abed Mohammed3,*, Mohamed Elhoseny4, Begonya Garcia-Zapirain5, Marwah Suliman Maashi6, Mashael S. Maashi7

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3161-3182, 2021, DOI:10.32604/cmc.2021.012691

    Abstract One of the most complex tasks for computer-aided diagnosis (Intelligent decision support system) is the segmentation of lesions. Thus, this study proposes a new fully automated method for the segmentation of ovarian and breast ultrasound images. The main contributions of this research is the development of a novel Viola–James model capable of segmenting the ultrasound images of breast and ovarian cancer cases. In addition, proposed an approach that can efficiently generate region-of-interest (ROI) and new features that can be used in characterizing lesion boundaries. This study uses two databases in training and testing the proposed… More >

  • Open Access


    Despeckling of Ultrasound Images Using Modified Local Statistics Mean Variance Filter

    Ranu Gupta1,3,*, Rahul Pachauri2,3, Ashutosh Singh1,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.1, pp. 19-32, 2018, DOI:10.3970/cmes.2018.114.019

    Abstract This article presents an improved method of despeckling the ultrasound medical images. In this paper a modified local statistics mean variance filter method has been proposed. In the proposed method, more consideration is given to local statistics since local statistical features are more important rather than global features.Various parameters like mean square error, peak signal to noise ratio, quality index, and structural similarity index measure are calculated to analyze the quality of the despeckled image. More >

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