Showing 1 - 19 results of 19 for search '(( binary each feature segmentation algorithm ) OR ( binary mask process optimization algorithm ))', query time: 0.57s Refine Results
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    A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

    Published 2025
    “…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. …”
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    Image processing workflow. by Denis Tamiev (7404980)

    Published 2020
    “…<p>Raw fluorescent microscope images (a) were processed with a binary segmentation algorithm, and clusters of bacterial cells were manually annotated. …”
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    PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

    Published 2023
    “…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …”
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    Key steps in neurodegeneration detection algorithm. by Andrew S. Clark (16510496)

    Published 2023
    “…Lastly, active contour segmentation of these features improves feature shape definition. …”
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    <b>Multimodal MRI radiomics</b><b> based on </b><b>habitat subregions of the tumor microenvironment</b><b> for predicting risk stratification in glioblastoma</b> by Han Wang (21457334)

    Published 2025
    “…Following segmentation, quantitative imaging phenomic (QIP) features were derived from each tumor subregion with the Cancer Imaging Phenomics Toolkit (CaPTk) in accordance with the guidelines established by the Image Biomarker Standardisation Initiative (IBSI).…”
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    Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) by Daniel Pérez Palau (11097348)

    Published 2024
    “…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”
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    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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    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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    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. …”