AI Medical Compendium Journal:
Journal of applied clinical medical physics

Showing 1 to 10 of 159 articles

Closing the gap in plan quality: Leveraging deep-learning dose prediction for adaptive radiotherapy.

Journal of applied clinical medical physics Mar 19, 2025
PURPOSE: Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re-optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a hi...
Head and Neck Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Algorithms Retrospective Studies Deep Learning Radiotherapy Dosage Radiotherapy, Intensity-Modulated Humans
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Enhanced dose prediction for head and neck cancer artificial intelligence-driven radiotherapy based on transfer learning with limited training data.

Journal of applied clinical medical physics Mar 14, 2025
PURPOSE: Training deep learning dose prediction models for the latest cutting-edge radiotherapy techniques, such as AI-based nodal radiotherapy (AINRT) and Daily Adaptive AI-based nodal radiotherapy (DA-AINRT), is challenging due to limited data. Thi...
Artificial Intelligence Algorithms Deep Learning Head and Neck Neoplasms Humans Radiotherapy, Intensity-Modulated Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage
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Bone-wise rigid registration of femur, tibia, and fibula for the tracking of temporal changes.

Journal of applied clinical medical physics Mar 11, 2025
BACKGROUND: Multiple myeloma (MM) induces temporal alterations in bone structure, such as osteolytic bone lesions, which are challenging to identify through manual image interpretation. The large variation in radiologists' assessments, even at expert...
Femur Fibula Algorithms Humans Tomography, X-Ray Computed Neural Networks, Computer Imaging, Three-Dimensional Image Processing, Computer-Assisted Multiple Myeloma Tibia
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Human papillomavirus (HPV) prediction for oropharyngeal cancer based on CT by using off-the-shelf features: A dual-dataset study.

Journal of applied clinical medical physics Mar 2, 2025
BACKGROUND: This study aims to develop a novel predictive model for determining human papillomavirus (HPV) presence in oropharyngeal cancer using computed tomography (CT). Current image-based HPV prediction methods are hindered by high computational ...
Neural Networks, Computer Algorithms Tomography, X-Ray Computed Humans Papillomavirus Infections Papillomaviridae Oropharyngeal Neoplasms Human Papillomavirus Viruses Female Male Image Processing, Computer-Assisted
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A knowledge-based planning model to identify fraction-reduction opportunities in brain stereotactic radiotherapy.

Journal of applied clinical medical physics Feb 21, 2025
OBJECTIVE: To develop and validate a HyperArc-based RapidPlan (HARP) model for three-fraction brain stereotactic radiotherapy (SRT) plans to then use to replan previously treated five-fraction SRT plans. Demonstrating the possibility of reducing the ...
Humans Organs at Risk Algorithms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Retrospective Studies Brain Neoplasms Knowledge Bases Radiotherapy, Intensity-Modulated Radiosurgery
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T2-weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study.

Journal of applied clinical medical physics Feb 20, 2025
PURPOSE: To compare image quality and clinical utility of a T2-weighted (T2W) 3-dimensional (3D) fast spin echo (FSE) sequence using deep learning reconstruction (DLR) versus conventional reconstruction for rectal magnetic resonance imaging (MRI).
Magnetic Resonance Imaging Rectal Neoplasms Retrospective Studies Deep Learning Female Humans Imaging, Three-Dimensional Aged Image Processing, Computer-Assisted Aged, 80 and over Adult Male Middle Aged
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Radiation oncology at crossroads: Rise of AI and managing the unexpected.

Journal of applied clinical medical physics Feb 17, 2025
Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflows, enhancing efficiency, safety, and quality. However, this transformation comes with a price of increased complexity and the emergence of unpredicta...
Humans Artificial Intelligence Patient Safety Risk Assessment Neoplasms Risk Management Radiation Oncology
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Evaluation and failure analysis of four commercial deep learning-based autosegmentation software for abdominal organs at risk.

Journal of applied clinical medical physics Feb 13, 2025
PURPOSE: Deep learning-based segmentation of organs-at-risk (OAR) is emerging to become mainstream in clinical practice because of the superior performance over atlas and model-based autocontouring methods. While several commercial deep learning-base...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Organs at Risk Radiotherapy Planning, Computer-Assisted Humans Software Algorithms
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The implementation of knowledge-based planning with partial OAR contours for prostate radiotherapy.

Journal of applied clinical medical physics Feb 7, 2025
PURPOSE: Intra- and inter-observer contour uncertainty is a continuous challenge in treatment planning for radiotherapy. Our proposed solution to address this challenge is the use of partial contours for treatment planning, focusing on uninvolved or ...
Knowledge Bases Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Retrospective Studies Male Prostatic Neoplasms Humans Artificial Intelligence Algorithms
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Evaluation of AI-based auto-contouring tools in radiotherapy: A single-institution study.

Journal of applied clinical medical physics Jan 21, 2025
BACKGROUND: Accurate delineation of organs at risk (OARs) is crucial yet time-consuming in the radiotherapy treatment planning workflow. Modern artificial intelligence (AI) technologies had made automation of OAR contouring feasible. This report deta...
Organs at Risk Algorithms Radiotherapy Planning, Computer-Assisted Neoplasms Radiotherapy Dosage Image Processing, Computer-Assisted Radiotherapy, Intensity-Modulated Humans Artificial Intelligence Software
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