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Showing 1 - 20 results of 21 for search 'multiple lesion detection algorithm', query time: 0.16s Refine Results
  1. 1
    Architecture for Tumor detection in esophageal Endoscopy images.

    Architecture for Tumor detection in esophageal Endoscopy images. by Young Seo Baik (21001443)

    Published 2025
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  2. 2
    Prediction results of a trained model for detecting the location of a tumor.

    Prediction results of a trained model for detecting the location of a tumor. by Young Seo Baik (21001443)

    Published 2025
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  3. 3
    Precision–recall curves obtained using the detection model for internal data.

    Precision–recall curves obtained using the detection model for internal data. by Young Seo Baik (21001443)

    Published 2025
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  4. 4
    Prediction results of a trained model for detecting the location of a tumor.

    Prediction results of a trained model for detecting the location of a tumor. by Young Seo Baik (21001443)

    Published 2025
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  5. 5
    TP predictions from a trained model for tumor location detection.

    TP predictions from a trained model for tumor location detection. by Young Seo Baik (21001443)

    Published 2025
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  6. 6
    Precision–recall curves obtained using the detection model for external data.

    Precision–recall curves obtained using the detection model for external data. by Young Seo Baik (21001443)

    Published 2025
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  7. 7
    TP predictions from a trained model for tumor location detection.

    TP predictions from a trained model for tumor location detection. by Young Seo Baik (21001443)

    Published 2025
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  8. 8
    Performance evaluation metrics for detection models based on confidence thresholds from external data.

    Performance evaluation metrics for detection models based on confidence thresholds from external data. by Young Seo Baik (21001443)

    Published 2025
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  9. 9
    Performance evaluation metrics for detection models based on confidence thresholds from internal data.

    Performance evaluation metrics for detection models based on confidence thresholds from internal data. by Young Seo Baik (21001443)

    Published 2025
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  10. 10
    Labeling data for regions of interest.

    Labeling data for regions of interest. by Young Seo Baik (21001443)

    Published 2025
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  11. 11
    Number of images collected for WLI/NBI data.

    Number of images collected for WLI/NBI data. by Young Seo Baik (21001443)

    Published 2025
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  12. 12
    Cell types, their morphology (Fig 1), detection, and disease association.

    Cell types, their morphology (Fig 1), detection, and disease association. by Soham Mandal (2854442)

    Published 2025
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  13. 13
    Trainable parameters for different algorithms.

    Trainable parameters for different algorithms. by Anwar Hossain Efat (19942283)

    Published 2024
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  14. 14
    Data Sheet 1_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.pdf

    Data Sheet 1_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.pdf by Dibash Basukala (20772110)

    Published 2025
    “…D<sub>t</sub> metrics were highly diagnostic as well as consistent along with f<sub>p</sub> metrics.</p>Discussion<p>Multiple 1<sub>st</sub> order radiomic features of D<sub>t</sub> and f<sub>p</sub> obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.…”
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  15. 15
    Image 2_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg

    Image 2_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

    Published 2025
    “…D<sub>t</sub> metrics were highly diagnostic as well as consistent along with f<sub>p</sub> metrics.</p>Discussion<p>Multiple 1<sub>st</sub> order radiomic features of D<sub>t</sub> and f<sub>p</sub> obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.…”
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  16. 16
    Image 4_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg

    Image 4_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

    Published 2025
    “…D<sub>t</sub> metrics were highly diagnostic as well as consistent along with f<sub>p</sub> metrics.</p>Discussion<p>Multiple 1<sub>st</sub> order radiomic features of D<sub>t</sub> and f<sub>p</sub> obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.…”
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  17. 17
    Image 3_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg

    Image 3_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

    Published 2025
    “…D<sub>t</sub> metrics were highly diagnostic as well as consistent along with f<sub>p</sub> metrics.</p>Discussion<p>Multiple 1<sub>st</sub> order radiomic features of D<sub>t</sub> and f<sub>p</sub> obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.…”
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  18. 18
    Image 1_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg

    Image 1_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

    Published 2025
    “…D<sub>t</sub> metrics were highly diagnostic as well as consistent along with f<sub>p</sub> metrics.</p>Discussion<p>Multiple 1<sub>st</sub> order radiomic features of D<sub>t</sub> and f<sub>p</sub> obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.…”
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  19. 19
    Image 5_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg

    Image 5_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

    Published 2025
    “…D<sub>t</sub> metrics were highly diagnostic as well as consistent along with f<sub>p</sub> metrics.</p>Discussion<p>Multiple 1<sub>st</sub> order radiomic features of D<sub>t</sub> and f<sub>p</sub> obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.…”
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  20. 20
    Data Sheet 1_A machine-learning approach for pancreatic neoplasia classification based on plasma extracellular vesicles.pdf

    Data Sheet 1_A machine-learning approach for pancreatic neoplasia classification based on plasma extracellular vesicles.pdf by Ioanna Angelioudaki (21177620)

    Published 2025
    “…EVs were detected and characterized by flow cytometry-immunostaining. …”
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