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Showing 1 - 4 results of 4 for search '(( binary task codon optimization algorithm ) OR ( binary also feature segmentation algorithm ))*', query time: 0.38s Refine Results
  1. 1
    The steps of proposed method of RWMA detection using echocardiography images for RWMA detection, consisting with cardiac structure segmentation using a trained U-Net on both A4C and A2C echo frames, resulting in segmented echo frames; motion features engineering with optical flow frames in both the A4C and A2C views, with backbone Temporal ConvNets to analysis the X and Y components of the motion; RWMA detection, using extracted features are fed into a suite of ML classifiers—including KNN, DT, Random Forest, SVM, and MLP—to achieve binary classification for the presence of RWMA or non-RWMA conditions.

    The steps of proposed method of RWMA detection using echocardiography images for RWMA detection, consisting with cardiac structure segmentation using a trained U-Net on both A4C an... by Sazzli Kasim (11218558)

    Published 2024
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  2. 2
    Table_2_Radiomics analysis of contrast-enhanced CT scans can distinguish between clear cell and non-clear cell renal cell carcinoma in different imaging protocols.docx

    Table_2_Radiomics analysis of contrast-enhanced CT scans can distinguish between clear cell and non-clear cell renal cell carcinoma in different imaging protocols.docx by Bettina Katalin Budai (13951317)

    Published 2022
    “…After the three-dimensional segmentation, 107 radiomics features (RFs) were extracted from the tumor volumes in each contrast phase. …”
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  3. 3
    Table_1_Radiomics analysis of contrast-enhanced CT scans can distinguish between clear cell and non-clear cell renal cell carcinoma in different imaging protocols.DOCX

    Table_1_Radiomics analysis of contrast-enhanced CT scans can distinguish between clear cell and non-clear cell renal cell carcinoma in different imaging protocols.DOCX by Bettina Katalin Budai (13951317)

    Published 2022
    “…After the three-dimensional segmentation, 107 radiomics features (RFs) were extracted from the tumor volumes in each contrast phase. …”
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  4. 4
    Data_Sheet_1_Radiomics analysis of contrast-enhanced CT scans can distinguish between clear cell and non-clear cell renal cell carcinoma in different imaging protocols.XLSX

    Data_Sheet_1_Radiomics analysis of contrast-enhanced CT scans can distinguish between clear cell and non-clear cell renal cell carcinoma in different imaging protocols.XLSX by Bettina Katalin Budai (13951317)

    Published 2022
    “…After the three-dimensional segmentation, 107 radiomics features (RFs) were extracted from the tumor volumes in each contrast phase. …”
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