Michael Dohopolski
Orcid: 0000-0002-9043-1490
According to our database1,
Michael Dohopolski
authored at least 13 papers
between 2019 and 2023.
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Bibliography
2023
Deep Learning (DL)-based Automatic Segmentation of the Internal Pudendal Artery (IPA) for Reduction of Erectile Dysfunction in Definitive Radiotherapy of Localized Prostate Cancer.
CoRR, 2023
2022
Prior Guided Deep Difference Meta-Learner for Fast Adaptation to Stylized Segmentation.
CoRR, 2022
Performance Deterioration of Deep Learning Models after Clinical Deployment: A Case Study with Auto-segmentation for Definitive Prostate Cancer Radiotherapy.
CoRR, 2022
Uncertainty estimations methods for a deep learning model to aid in clinical decision-making - a clinician's perspective.
CoRR, 2022
Recurrence-free Survival Prediction under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers.
CoRR, 2022
Exploring the combination of deep-learning based direct segmentation and deformable image registration for cone-beam CT based auto-segmentation for adaptive radiotherapy.
CoRR, 2022
Recurrence-Free Survival Prediction Under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers.
Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2022
2021
A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy.
Medical Image Anal., 2021
CoRR, 2021
PSA-Net: Deep Learning based Physician Style-Aware Segmentation Network for Post-Operative Prostate Cancer Clinical Target Volume.
CoRR, 2021
PSA-Net: Deep learning-based physician style-aware segmentation network for postoperative prostate cancer clinical target volumes.
Artif. Intell. Medicine, 2021
2019
Reliable lymph node metastasis prediction in head & neck cancer through automated multi-objective model.
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019