4.1 Review

Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Engineering, Biomedical

Probabilistic dose prediction using mixture density networks for automated radiation therapy treatment planning

Viktor Nilsson et al.

Summary: Mixture Density Networks (MDNs) can effectively predict dose distributions and reflect uncertain decision making in clinical tradeoffs. Testing shows that MDNs follow the real situation well spatially and in terms of dose-volume, indicating the potential to support clinical management and improve the quality of automated treatment planning.

PHYSICS IN MEDICINE AND BIOLOGY (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Expanding the medical physicist curricular and professional programme to include Artificial Intelligence

F. Zanca et al.

Summary: This AI curriculum is the first attempt to expand the current educational framework for Medical Physicists in Europe, and should be considered as a document to top the sub-specialties' curriculums and adapted by national training and regulatory bodies. The proposed educational program can be implemented via the European School of Medical Physics Expert (ESMPE) course modules and - to some extent - also by the national competent EFOMP organizations, to reach widely the medical physicist community in Europe.

PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2021)

Article Oncology

Development and evaluation of radiotherapy deep learning dose prediction models for breast cancer

Nienke Bakx et al.

Summary: This study evaluated the performance of two machine learning models for breast cancer radiotherapy, finding slight discrepancies in evaluation criteria after mimicking, with no clinically relevant differences in doses to OARs. Both models show potential for automated treatment planning in breast cancer.

PHYSICS & IMAGING IN RADIATION ONCOLOGY (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Knowledge-based automated planning with three-dimensional generative adversarial networks

Aaron Babier et al.

MEDICAL PHYSICS (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

The importance of evaluating the complete automated knowledge-based planning pipeline

Aaron Babier et al.

PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Artificial intelligence-based radiotherapy machine parameter optimization using reinforcement learning

William Thomas Hrinivich et al.

MEDICAL PHYSICS (2020)

Article Engineering, Biomedical

Deep learning-based inverse mapping for fluence map prediction

Lin Ma et al.

PHYSICS IN MEDICINE AND BIOLOGY (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Evaluation of optimization workflow using custom-made planning through predicted dose distribution for head and neck tumor treatment

Kentaro Miki et al.

PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2020)

Article Computer Science, Artificial Intelligence

Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy

Wentao Wang et al.

FRONTIERS IN ARTIFICIAL INTELLIGENCE (2020)

Review Radiology, Nuclear Medicine & Medical Imaging

Knowledge-based planning for intensity-modulated radiation therapy: A review of data-driven approaches

Yaorong Ge et al.

MEDICAL PHYSICS (2019)

Review Oncology

Artificial Intelligence in Radiotherapy Treatment Planning: Present and Future

Chunhao Wang et al.

TECHNOLOGY IN CANCER RESEARCH & TREATMENT (2019)

Review Radiology, Nuclear Medicine & Medical Imaging

Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations

Mohammad Hussein et al.

BRITISH JOURNAL OF RADIOLOGY (2018)