AIMC Topic: Radiotherapy Planning, Computer-Assisted

Clear Filters Showing 141 to 150 of 778 articles

Machine learning in image-based outcome prediction after radiotherapy: A review.

Journal of applied clinical medical physics Nov 18, 2024
The integration of machine learning (ML) with radiotherapy has emerged as a pivotal innovation in outcome prediction, bringing novel insights amid unique challenges. This review comprehensively examines the current scope of ML applications in various...
Radiotherapy Dosage Humans Machine Learning Neoplasms Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted
View on PubMed DOI

Prior information guided deep-learning model for tumor bed segmentation in breast cancer radiotherapy.

BMC medical imaging Nov 18, 2024
BACKGROUND AND PURPOSE: Tumor bed (TB) is the residual cavity of resected tumor after surgery. Delineating TB from CT is crucial in generating clinical target volume for radiotherapy. Due to multiple surgical effects and low image contrast, segmentin...
Radiotherapy, Image-Guided Breast Neoplasms Humans Deep Learning Tomography, X-Ray Computed Radiotherapy Planning, Computer-Assisted Female
View on PubMed DOI

Attention 3D UNET for dose distribution prediction of high-dose-rate brachytherapy of cervical cancer: Intracavitary applicators.

Journal of applied clinical medical physics Nov 15, 2024
BACKGROUND: Formulating a clinically acceptable plan within the time-constrained clinical setting of brachytherapy poses challenges to clinicians. Deep learning based dose prediction methods have shown favorable solutions for enhancing efficiency, bu...
Retrospective Studies Female Uterine Cervical Neoplasms Radiotherapy Planning, Computer-Assisted Brachytherapy Radiotherapy Dosage Deep Learning Humans Radiotherapy, Intensity-Modulated Imaging, Three-Dimensional Algorithms Organs at Risk
View on PubMed DOI

Deep learning based ultra-low dose fan-beam computed tomography image enhancement algorithm: Feasibility study in image quality for radiotherapy.

Journal of applied clinical medical physics Nov 14, 2024
OBJECTIVE: We investigated the feasibility of deep learning-based ultra-low dose kV-fan-beam computed tomography (kV-FBCT) image enhancement algorithm for clinical application in abdominal and pelvic tumor radiotherapy.
Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Organs at Risk Radiotherapy Planning, Computer-Assisted Tomography, X-Ray Computed Female Male Humans Algorithms Prospective Studies Radiotherapy Dosage Abdominal Neoplasms Radiotherapy, Intensity-Modulated Radiotherapy, Image-Guided Radiation Dosage Phantoms, Imaging Radiographic Image Enhancement Signal-To-Noise Ratio Pelvic Neoplasms
View on PubMed DOI

Understanding and modeling human-AI interaction of artificial intelligence tool in radiation oncology clinic using deep neural network: a feasibility study using three year prospective data.

Physics in medicine and biology Nov 14, 2024
Artificial intelligence (AI) based treatment planning tools are being implemented in clinic. However, human interactions with such AI tools are rarely analyzed. This study aims to comprehend human planner's interaction with the AI planning tool and i...
Neural Networks, Computer Humans Time Factors Feasibility Studies Artificial Intelligence Female Radiotherapy Planning, Computer-Assisted Radiation Oncology Prospective Studies Breast Neoplasms Deep Learning
View on PubMed DOI

Deep learning prediction of scenario doses for direct plan robustness evaluations in IMPT for head-and-neck.

Physics in medicine and biology Nov 12, 2024
. Intensity modulated proton therapy (IMPT) is susceptible to uncertainties in patient setup and proton range. Robust optimization is employed in IMPT treatment planning to ensure sufficient coverage of the clinical target volume (CTV) in predefined ...
Radiotherapy, Intensity-Modulated Proton Therapy Deep Learning Radiotherapy Planning, Computer-Assisted Head and Neck Neoplasms Radiation Dosage Humans Radiotherapy Dosage Tomography, X-Ray Computed
View on PubMed DOI

The Segment Anything foundation model achieves favorable brain tumor auto-segmentation accuracy in MRI to support radiotherapy treatment planning.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] Nov 6, 2024
BACKGROUND: Promptable foundation auto-segmentation models like Segment Anything (SA, Meta AI, New York, USA) represent a novel class of universal deep learning auto-segmentation models that could be employed for interactive tumor auto-contouring in ...
Humans Magnetic Resonance Imaging Radiotherapy Planning, Computer-Assisted Brain Neoplasms Deep Learning Glioma
View on PubMed DOI

Clinical commissioning and introduction of an in-house artificial intelligence (AI) platform for automated head and neck intensity modulated radiation therapy (IMRT) treatment planning.

Journal of applied clinical medical physics Nov 6, 2024
BACKGROUND AND PURPOSE: To describe the clinical commissioning of an in-house artificial intelligence (AI) treatment planning platform for head-and-neck (HN) Intensity Modulated Radiation Therapy (IMRT).
Humans Artificial Intelligence Radiotherapy, Intensity-Modulated Algorithms Organs at Risk User-Computer Interface Radiotherapy Planning, Computer-Assisted Head and Neck Neoplasms Radiotherapy Dosage
View on PubMed DOI

Automatic delineation of cervical cancer target volumes in small samples based on multi-decoder and semi-supervised learning and clinical application.

Scientific reports Nov 6, 2024
Radiotherapy has been demonstrated to be one of the most significant treatments for cervical cancer, during which accurate and efficient delineation of target volumes is critical. To alleviate the data demand of deep learning and promote the establis...
Supervised Machine Learning Radiotherapy Planning, Computer-Assisted Uterine Cervical Neoplasms Middle Aged Deep Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Female Aged Adult Humans
View on PubMed DOI

Assessment of pencil beam scanning proton therapy beam delivery accuracy through machine learning and log file analysis.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Nov 1, 2024
PURPOSE: Comprehensive Quality Assurance (QA) protocols are necessary for complex beam delivery systems like Pencil Beam Scanning (PBS) proton therapy. This study focuses on automating the evaluation of beam delivery accuracy using irradiation log fi...
Radiotherapy Dosage Proton Therapy Humans Machine Learning Quality Control Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care
View on PubMed DOI
Popular Topics
Recent Journals