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  • Open Access

    ARTICLE

    Hybrid MNLTP Texture Descriptor and PDCNN-Based OCT Image Classification for Retinal Disease Detection

    Jahida Subhedar1,2, Anurag Mahajan1,*, Shabana Urooj3, Neeraj Kumar Shukla4,5

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2831-2847, 2025, DOI:10.32604/cmc.2025.059350 - 17 February 2025

    Abstract Retinal Optical Coherence Tomography (OCT) images, a non-invasive imaging technique, have become a standard retinal disease detection tool. Due to disease, there are morphological and textural changes in the layers of the retina. Classifying OCT images is challenging, as the morphological manifestations of different diseases may be similar. The OCT images capture the reflectivity characteristics of the retinal tissues. Retinal diseases change the reflectivity property of retinal tissues, resulting in texture variations in OCT images. We propose a hybrid approach to OCT image classification in which the Convolution Neural Network (CNN) model is trained using… More >

  • Open Access

    ARTICLE

    3D Reconstruction for Early Detection of Liver Cancer

    Rana Mohamed1,2,*, Mostafa Elgendy1, Mohamed Taha1

    Computer Systems Science and Engineering, Vol.49, pp. 213-238, 2025, DOI:10.32604/csse.2024.059491 - 10 January 2025

    Abstract Globally, liver cancer ranks as the sixth most frequent malignancy cancer. The importance of early detection is undeniable, as liver cancer is the fifth most common disease in men and the ninth most common cancer in women. Recent advances in imaging, biomarker discovery, and genetic profiling have greatly enhanced the ability to diagnose liver cancer. Early identification is vital since liver cancer is often asymptomatic, making diagnosis difficult. Imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and ultrasonography can be used to identify liver cancer once a sample of liver tissue is… More >

  • Open Access

    PROCEEDINGS

    Effects of Hatch Spacing on Pore Segregation and Mechanical Properties During Blue Laser Directed Energy Deposition of AlSi10Mg

    Hongze Wang1,2,3,*, An Wang1,2, Zijue Tang1,2, Yi Wu1,2,3, Haowei Wang1,2,3,4

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012430

    Abstract Hatch spacing is a crucial parameter for achieving superior mechanical properties during the process of laser directed energy deposition (L-DED) process. However, the optimum hatch spacing is based on trial and error approaches using pre-existing experience. In this paper, we have systematically compared the porosity characteristics, microstructure evolution, and thermal gradients in double tracks of AlSi10Mg under various hatch spacings during blue laser directed energy deposition (BL-DED). A peculiar phenomenon of pore segregation is observed at the boundary of the overlapping zone of adjacent deposited tracks, where the porosity is almost 8 times that of… More >

  • Open Access

    REVIEW

    A Survey of Lung Nodules Detection and Classification from CT Scan Images

    Salman Ahmed1, Fazli Subhan2,3, Mazliham Mohd Su’ud3,*, Muhammad Mansoor Alam3,4, Adil Waheed5

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1483-1511, 2024, DOI:10.32604/csse.2024.053997 - 22 November 2024

    Abstract In the contemporary era, the death rate is increasing due to lung cancer. However, technology is continuously enhancing the quality of well-being. To improve the survival rate, radiologists rely on Computed Tomography (CT) scans for early detection and diagnosis of lung nodules. This paper presented a detailed, systematic review of several identification and categorization techniques for lung nodules. The analysis of the report explored the challenges, advancements, and future opinions in computer-aided diagnosis CAD systems for detecting and classifying lung nodules employing the deep learning (DL) algorithm. The findings also highlighted the usefulness of DL… More >

  • Open Access

    PROCEEDINGS

    Characterization on Fracture Toughness of Cermet Coating Coupling Instrumented Indentation and X-Ray Computed Tomography

    Ruizhe Huang1, Zhaoliang Qu1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011440

    Abstract The surface brittle fracture of cermet coating seriously restricts its application. Accurate evaluation of the fracture toughness of cermet coating is a prerequisite for improving its life. This paper aims to propose an accurate characterization method for fracture toughness of cermet coating. By coupling instrumented indentation and X‑ ray computed tomography, the indentation-induced fracture behaviors under various loads within WC-12%Co coatings were studied. The indentation response was correlated with the damage evolution directly observed within the coating. The impact of substrate effects on indentation-induced fracture behaviors was further studied using finite element analysis (FEA). The… More >

  • Open Access

    ARTICLE

    Enhancing Multi-Modality Medical Imaging: A Novel Approach with Laplacian Filter + Discrete Fourier Transform Pre-Processing and Stationary Wavelet Transform Fusion

    Mian Muhammad Danyal1,2, Sarwar Shah Khan3,4,*, Rahim Shah Khan5, Saifullah Jan2, Naeem ur Rahman6

    Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 35-53, 2024, DOI:10.32604/jimh.2024.051340 - 08 July 2024

    Abstract Multi-modality medical images are essential in healthcare as they provide valuable insights for disease diagnosis and treatment. To harness the complementary data provided by various modalities, these images are amalgamated to create a single, more informative image. This fusion process enhances the overall quality and comprehensiveness of the medical imagery, aiding healthcare professionals in making accurate diagnoses and informed treatment decisions. In this study, we propose a new hybrid pre-processing approach, Laplacian Filter + Discrete Fourier Transform (LF+DFT), to enhance medical images before fusion. The LF+DFT approach highlights key details, captures small information, and sharpens… More >

  • Open Access

    ARTICLE

    Positron Emission Tomography Lung Image Respiratory Motion Correcting with Equivariant Transformer

    Jianfeng He1,2, Haowei Ye1, Jie Ning1, Hui Zhou1,2,*, Bo She3,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3355-3372, 2024, DOI:10.32604/cmc.2024.048706 - 15 May 2024

    Abstract In addressing the challenge of motion artifacts in Positron Emission Tomography (PET) lung scans, our study introduces the Triple Equivariant Motion Transformer (TEMT), an innovative, unsupervised, deep-learning-based framework for efficient respiratory motion correction in PET imaging. Unlike traditional techniques, which segment PET data into bins throughout a respiratory cycle and often face issues such as inefficiency and overemphasis on certain artifacts, TEMT employs Convolutional Neural Networks (CNNs) for effective feature extraction and motion decomposition.TEMT’s unique approach involves transforming motion sequences into Lie group domains to highlight fundamental motion patterns, coupled with employing competitive weighting for More >

  • Open Access

    ARTICLE

    Material-SAM: Adapting SAM for Material XCT

    Xuelong Wu1, Junsheng Wang1,*, Zhongyao Li1, Yisheng Miao1, Chengpeng Xue1, Yuling Lang2, Decai Kong2, Xiaoying Ma2, Haibao Qiao2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3703-3720, 2024, DOI:10.32604/cmc.2024.047027 - 26 March 2024

    Abstract X-ray Computed Tomography (XCT) enables non-destructive acquisition of the internal structure of materials, and image segmentation plays a crucial role in analyzing material XCT images. This paper proposes an image segmentation method based on the Segment Anything model (SAM). We constructed a dataset of carbide in nickel-based single crystal superalloys XCT images and preprocessed the images using median filtering, histogram equalization, and gamma correction. Subsequently, SAM was fine-tuned to adapt to the task of material XCT image segmentation, resulting in Material-SAM. We compared the performance of threshold segmentation, SAM, U-Net model, and Material-SAM. Our method More >

  • Open Access

    ARTICLE

    Multilevel Attention Unet Segmentation Algorithm for Lung Cancer Based on CT Images

    Huan Wang1, Shi Qiu1,2,*, Benyue Zhang1, Lixuan Xiao3

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1569-1589, 2024, DOI:10.32604/cmc.2023.046821 - 27 February 2024

    Abstract Lung cancer is a malady of the lungs that gravely jeopardizes human health. Therefore, early detection and treatment are paramount for the preservation of human life. Lung computed tomography (CT) image sequences can explicitly delineate the pathological condition of the lungs. To meet the imperative for accurate diagnosis by physicians, expeditious segmentation of the region harboring lung cancer is of utmost significance. We utilize computer-aided methods to emulate the diagnostic process in which physicians concentrate on lung cancer in a sequential manner, erect an interpretable model, and attain segmentation of lung cancer. The specific advancements… More >

  • Open Access

    REVIEW

    Congenital Absence of Pericardium: The Largest Systematic Review in the Field on 247 Worldwide Cases (1977-Now)

    Pier Paolo Bassareo1,2,3,*, Aurelio Secinaro4, Paolo Ciliberti5, Massimo Chessa6,7, Marco Alfonso Perrone5,8, Kevin Patrick Walsh1,2,3, Colin Joseph Mcmahon2,3

    Congenital Heart Disease, Vol.18, No.6, pp. 595-610, 2023, DOI:10.32604/chd.2023.046229 - 19 January 2024

    Abstract Background: Congenital absence of pericardium (CAP), also known as pericardial agenesis, represents an uncommon cardiac abnormality and mostly incidental finding. It can be subdivided into complete and partial (left or right-sided) forms. Because of its infrequency, just case reports and a few case series have been released so far. This paper represents the largest systematic review in the field. Nine features (age at diagnosis, type, gender, clinical presentation, electrocardiography, imaging (ultrasounds, CT/MRI), concomitant cardiac defects, and outcome) were analysed. Methods: The electronic database PubMed was investigated from its establishment up to July 15th, 2023. Just case… More >

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