Search Results - "Bluemink, Hanneke"

Development and evaluation of radiotherapy deep learning dose prediction models for breast cancer by Bakx, Nienke, Bluemink, Hanneke, Hagelaar, Els, van der Sangen, Maurice, Theuws, Jacqueline, Hurkmans, Coen

“…Treatment planning of radiotherapy is a time-consuming and planner dependent process that can be automated by dose prediction models. The purpose of this study…”
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Comparison of the output of a deep learning segmentation model for locoregional breast cancer radiotherapy trained on 2 different datasets by Bakx, Nienke, van der Sangen, Maurice, Theuws, Jacqueline, Bluemink, Hanneke, Hurkmans, Coen

“…•The effect of training a deep learning model on different training data was evaluated.•An external model was compared to an in-house model and evaluated to…”
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Clinical evaluation of two AI models for automated breast cancer plan generation by Kneepkens, Esther, Bakx, Nienke, van der Sangen, Maurice, Theuws, Jacqueline, van der Toorn, Peter-Paul, Rijkaart, Dorien, van der Leer, Jorien, van Nunen, Thérèse, Hagelaar, Els, Bluemink, Hanneke, Hurkmans, Coen

“…Artificial intelligence (AI) shows great potential to streamline the treatment planning process. However, its clinical adoption is slow due to the limited…”
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Artificial intelligence based treatment planning of radiotherapy for locally advanced breast cancer by van de Sande, Dennis, Sharabiani, Marjan, Bluemink, Hanneke, Kneepkens, Esther, Bakx, Nienke, Hagelaar, Els, van der Sangen, Maurice, Theuws, Jacqueline, Hurkmans, Coen

“…Treatment planning of radiotherapy for locally advanced breast cancer patients can be a time consuming process. Artificial intelligence based treatment…”
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Reduction of heart and lung normal tissue complication probability using automatic beam angle optimization and more generic optimization objectives for breast radiotherapy by Bakx, Nienke, Bluemink, Hanneke, Hagelaar, Els, van der Leer, Jorien, van der Sangen, Maurice, Theuws, Jacqueline, Hurkmans, Coen

“…During breast cancer radiotherapy, sparing of healthy tissue is desired. The effect of automatic beam angle optimization and generic dose fall-off objectives…”
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Clinical evaluation of a deep learning segmentation model including manual adjustments afterwards for locally advanced breast cancer by Bakx, Nienke, Rijkaart, Dorien, van der Sangen, Maurice, Theuws, Jacqueline, van der Toorn, Peter-Paul, Verrijssen, An-Sofie, van der Leer, Jorien, Mutsaers, Joline, van Nunen, Thérèse, Reinders, Marjon, Schuengel, Inge, Smits, Julia, Hagelaar, Els, van Gruijthuijsen, Dave, Bluemink, Johanna, Hurkmans, Coen

“…•A deep learning segmentation model was trained for locally advanced breast cancer.•Both quantitative and qualitative analysis was used for evaluation.•Time…”
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