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- 2024
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Mark
Enhanced classification performance using deep learning based segmentation for pulmonary embolism detection in CT angiography
(
- Contribution to journal › Article
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Mark
A Simple End-to-End Computer-Aided Detection Pipeline for Trained Deep Learning Models
2024) 8th International Conference on Engineering of Computer-Based Systems, ECBS 2023 In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 14390 LNCS. p.259-262(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Evaluation of a deep learning magnetic resonance imaging reconstruction method for synthetic computed tomography generation in prostate radiotherapy
(
- Contribution to journal › Article
- 2023
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Mark
MRI-only radiotherapy from an economic perspective : Can new techniques in prostate cancer treatment be cost saving?
(
- Contribution to journal › Article
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Mark
Geometric impact and dose estimation of on-patient placement of a lightweight receiver coil in a clinical magnetic resonance imaging-only radiotherapy workflow for prostate cancer
(
- Contribution to journal › Article
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Mark
FLASH radiotherapy and the associated dosimetric challenges
(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Deep learning-based classification of organs at risk and delineation guideline in pelvic cancer radiation therapy
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- Contribution to journal › Article
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Mark
Polymer gel dosimetry for experimental verification of conformal small animal irradiation at a preclinical research platform
2023) 12th International Conference on 3D and Advanced Dosimetry, IC3DDose 2022 In Journal of Physics: Conference Series 2630(1).(
- Contribution to journal › Article
- 2022
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Mark
Tensor-valued diffusion magnetic resonance imaging in a radiotherapy setting
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- Contribution to journal › Article
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Mark
Evalutation of two commercial deep learning OAR segmentation models for prostate cancer treatment
2022) ESTRO 2022(
- Contribution to conference › Abstract