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  • Open Access


    Classification of Multi-view Digital Mammogram Images Using SMO-WkNN

    P. Malathi1,*, G. Charlyn Pushpa Latha2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1741-1758, 2023, DOI:10.32604/csse.2023.035185

    Abstract Breast cancer (BCa) is a leading cause of death in the female population across the globe. Approximately 2.3 million new BCa cases are recorded globally in females, overtaking lung cancer as the most prevalent form of cancer to be diagnosed. However, the mortality rates for cervical and BCa are significantly higher in developing nations than in developed countries. Early diagnosis is the only option to minimize the risks of BCa. Deep learning (DL)-based models have performed well in image processing in recent years, particularly convolutional neural network (CNN). Hence, this research proposes a DL-based CNN model to diagnose BCa from… More >

  • Open Access


    Classification of Liver Tumors from Computed Tomography Using NRSVM

    S. Priyadarsini1,*, Carlos Andrés Tavera Romero2, M. Mrunalini3, Ganga Rama Koteswara Rao4, Sudhakar Sengan5

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1517-1530, 2022, DOI:10.32604/iasc.2022.024786

    Abstract A classification system is used for Benign Tumors (BT) and Malignant Tumors (MT) in the abdominal liver. Computed Tomography (CT) images based on enhanced RGS is proposed. Diagnosis of liver diseases based on observation using liver CT images is essential for surgery and treatment planning. Identifying the progression of cancerous regions and Classification into Benign Tumors and Malignant Tumors are essential for treating liver diseases. The manual process is time-consuming and leads to intra and inter-observer variability. Hence, an automatic method based on enhanced region growing is proposed for the Classification of Liver Tumors (LT). To enhance the Liver Region… More >

  • Open Access


    IoMT Enabled Melanoma Detection Using Improved Region Growing Lesion Boundary Extraction

    Tanzila Saba1, Rabia Javed2,3, Mohd Shafry Mohd Rahim2, Amjad Rehman1,*, Saeed Ali Bahaj4

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6219-6237, 2022, DOI:10.32604/cmc.2022.020865

    Abstract The Internet of Medical Things (IoMT) and cloud-based healthcare applications, services are beneficial for better decision-making in recent years. Melanoma is a deadly cancer with a higher mortality rate than other skin cancer types such as basal cell, squamous cell, and Merkel cell. However, detection and treatment at an early stage can result in a higher chance of survival. The classical methods of detection are expensive and labor-intensive. Also, they rely on a trained practitioner's level, and the availability of the needed equipment is essential for the early detection of Melanoma. The current improvement in computer-aided systems is providing very… More >

  • Open Access


    Identification and Segmentation of Impurities Accumulated in a Cold-Trap Device by Using Radiographic Images

    Thamotharan B1,*, Venkatraman B2, Chandrasekaran S3

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 335-340, 2020, DOI:10.31209/2019.100000156

    Abstract Accumulation of impurities within cold trap device results in degradation of efficient performance in a nuclear reactor systems. The impurities have to be identified and the device has to be replaced periodically based on the accumulation level. Though there are a few techniques available to identify these impurities from the cold trap device, there are certain limitations in these techniques. In order to overcome these constraints, a new harmless and easy approach for identifying and separating the impurities using the radiographic images of cold traps is proposed in this paper. It includes a new segmentation algorithm to segregate the deposited… More >

  • Open Access


    Ultrasound Speckle Reduction Based on Histogram Curve Matching and Region Growing

    Jinrong Hu1, Zhiqin Lei1, Xiaoying Li2, *, Yongqun He3, Jiliu Zhou1

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 705-722, 2020, DOI:10.32604/cmc.2020.09878

    Abstract The quality of ultrasound scanning images is usually damaged by speckle noise. This paper proposes a method based on local statistics extracted from a histogram to reduce ultrasound speckle through a region growing algorithm. Unlike single statistical moment-based speckle reduction algorithms, this method adaptively smooths the speckle regions while preserving the margin and tissue structure to achieve high detectability. The criterion of a speckle region is defined by the similarity value obtained by matching the histogram of the current processing window and the reference window derived from the speckle region in advance. Then, according to the similarity value and tissue… More >

  • Open Access


    A Fast Filling Algorithm for Image Restoration Based on Contour Parity

    Yan Liu1, *, Wenxin Hu1, *, Longzhe Han2, Maksymyuk Taras3, Zhiyun Chen1

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 509-519, 2020, DOI:10.32604/cmc.2020.07519

    Abstract Filling techniques are often used in the restoration of images. Yet the existing filling technique approaches either have high computational costs or present problems such as filling holes redundantly. This paper proposes a novel algorithm for filling holes and regions of the images. The proposed algorithm combines the advantages of both the parity-check filling approach and the region-growing inpainting technique. Pairing points of the region’s boundary are used to search and to fill the region. The scanning range of the filling method is within the target regions. The proposed method does not require additional working memory or assistant colors, and… More >

  • Open Access


    Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

    Qili Zhou1, Yongbin Qiu1, Li Li1,*, Jianfeng Lu1, Wenqiang Yuan1, Xiaoqing Feng2, Xiaoyang Mao3

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 151-163, 2018, DOI:10.3970/cmc.2018.055.151

    Abstract Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture.… More >

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