Search Results - Löfman, Fredrik

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  1. 1
    Artificial intelligence and machine learning for medical imaging: A technology review

    Artificial intelligence and machine learning for medical imaging: A technology review by Barragán-Montero, Ana, Javaid, Umair, Valdés, Gilmer, Nguyen, Dan, Desbordes, Paul, Macq, Benoit, Willems, Siri, Vandewinckele, Liesbeth, Holmström, Mats, Löfman, Fredrik, Michiels, Steven, Souris, Kevin, Sterpin, Edmond, Lee, John A.

    Published in Physica medica
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  2. 2
    Automated delineation of the clinical target volume using anatomically constrained 3D expansion of the gross tumor volume

    Automated delineation of the clinical target volume using anatomically constrained 3D expansion of the gross tumor volume by Shusharina, Nadya, Söderberg, Jonas, Edmunds, David, Löfman, Fredrik, Shih, Helen, Bortfeld, Thomas

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  3. 3
    Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency

    Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency by Barragán-Montero, Ana, Bibal, Adrien, Dastarac, Margerie Huet, Draguet, Camille, Valdés, Gilmer, Nguyen, Dan, Willems, Siri, Vandewinckele, Liesbeth, Holmström, Mats, Löfman, Fredrik, Souris, Kevin, Sterpin, Edmond, Lee, John A

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  4. 4
    Machine learning-based detection of aberrant deep learning segmentations of target and organs at risk for prostate radiotherapy using a secondary segmentation algorithm

    Machine learning-based detection of aberrant deep learning segmentations of target and organs at risk for prostate radiotherapy using a secondary segmentation algorithm by Claessens, Michaël, Vanreusel, Verdi, De Kerf, Geert, Mollaert, Isabelle, Löfman, Fredrik, Gooding, Mark J, Brouwer, Charlotte, Dirix, Piet, Verellen, Dirk

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  5. 5
    Clinical implementation of deep learning robust IMPT planning in oropharyngeal cancer patients: A blinded clinical study

    Clinical implementation of deep learning robust IMPT planning in oropharyngeal cancer patients: A blinded clinical study by van Bruggen, Ilse G., van Dijk, Marije, Brinkman-Akker, Minke J., Löfman, Fredrik, Langendijk, Johannes A., Both, Stefan, Korevaar, E.W.

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  6. 6
    Comparison of Vendor-Pretrained and Custom-Trained Deep Learning Segmentation Models for Head-and-Neck, Breast, and Prostate Cancers

    Comparison of Vendor-Pretrained and Custom-Trained Deep Learning Segmentation Models for Head-and-Neck, Breast, and Prostate Cancers by Chen, Xinru, Zhao, Yao, Baroudi, Hana, El Basha, Mohammad D, Daniel, Aji, Gay, Skylar S, Yu, Cenji, Wang, He, Phan, Jack, Choi, Seungtaek L, Goodman, Chelain R, Zhang, Xiaodong, Niedzielski, Joshua S, Shete, Sanjay S, Court, Laurence E, Liao, Zhongxing, Löfman, Fredrik, Balter, Peter A, Yang, Jinzhong

    Published in Diagnostics (Basel)
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  7. 7
    Pareto Dose Prediction Using Fully Convolutional Networks Operating in 3D

    Pareto Dose Prediction Using Fully Convolutional Networks Operating in 3D by Nordström, Marcus, Hult, Henrik, Maki, Atsuto, Löfman, Fredrik

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  8. 8
    Noisy Image Segmentation With Soft-Dice

    Noisy Image Segmentation With Soft-Dice by Nordström, Marcus, Hult, Henrik, Maki, Atsuto, Löfman, Fredrik

    Published in arXiv.org
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  9. 9
    On Image Segmentation With Noisy Labels: Characterization and Volume Properties of the Optimal Solutions to Accuracy and Dice

    On Image Segmentation With Noisy Labels: Characterization and Volume Properties of the Optimal Solutions to Accuracy and Dice by Nordström, Marcus, Hult, Henrik, Söderberg, Jonas, Löfman, Fredrik

    Published in arXiv.org
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