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    Bi-level Analysis of Computed Tomography Images of Malignant Pleural Mesothelioma: Deep Learning-Based Classification and Subsequent Three-Dimensional Reconstruction 

    Source: Journal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 006:;page 64501-1
    Author(s): Weiss Cohen, Miri; Ghidotti, Anna; Regazzoni, Daniele
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A bi-level analysis of computed tomography (CT) images of malignant pleural mesothelioma (MPM) is presented in this paper, starting with a deep learning-based system for classification, followed by a three-dimensional (3D) ...
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    Evaluation of Clinical and Technical Parameters to Customize Total Knee Arthroplasty Implants 

    Source: Journal of Computing and Information Science in Engineering:;2022:;volume( 022 ):;issue: 006:;page 61006
    Author(s): Ghidotti, Anna;Landi, Daniele;Regazzoni, Daniele;Rizzi, Caterina
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Since every structure in the human body can vary, customization is important to choose the most appropriate medical option according to the patient. Total knee arthroplasty (TKA) is a surgical procedure for the knee ...
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    Comparative Analysis of Convolutional Neural Network Architectures for Automated Knee Segmentation in Medical Imaging: A Performance Evaluation 

    Source: Journal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 005:;page 51006-1
    Author(s): Ghidotti, Anna; Vitali, Andrea; Regazzoni, Daniele; Cohen, Miri Weiss; Rizzi, Caterina
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Segmentation of anatomical components is a major step in creating accurate and realistic 3D models of the human body, which are used in many clinical applications, including orthopedics. Recently, many deep learning ...
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