AI Medical Compendium Journal:
Journal of applied clinical medical physics

Showing 31 to 40 of 159 articles

Evaluation of deep learning based dose prediction in head and neck cancer patients using two different types of input contours.

Journal of applied clinical medical physics Sep 16, 2024
PURPOSE: This study evaluates deep learning (DL) based dose prediction methods in head and neck cancer (HNC) patients using two types of input contours.
Radiotherapy Planning, Computer-Assisted Humans Radiotherapy Dosage Software Radiotherapy, Intensity-Modulated Algorithms Prognosis Deep Learning Head and Neck Neoplasms Organs at Risk
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Automated confidence estimation in deep learning auto-segmentation for brain organs at risk on MRI for radiotherapy.

Journal of applied clinical medical physics Sep 16, 2024
PURPOSE: We have built a novel AI-driven QA method called AutoConfidence (ACo), to estimate segmentation confidence on a per-voxel basis without gold standard segmentations, enabling robust, efficient review of automated segmentation (AS). We have de...
Humans Algorithms Retrospective Studies Brain Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Deep Learning Image Processing, Computer-Assisted Glioma Magnetic Resonance Imaging
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Artificial intelligence-based motion tracking in cancer radiotherapy: A review.

Journal of applied clinical medical physics Aug 28, 2024
Radiotherapy aims to deliver a prescribed dose to the tumor while sparing neighboring organs at risk (OARs). Increasingly complex treatment techniques such as volumetric modulated arc therapy (VMAT), stereotactic radiosurgery (SRS), stereotactic body...
Artificial Intelligence Humans Algorithms Radiotherapy Planning, Computer-Assisted Neoplasms Radiotherapy Dosage Organs at Risk Radiotherapy, Intensity-Modulated Movement
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Non-coplanar CBCT image reconstruction using a generative adversarial network for non-coplanar radiotherapy.

Journal of applied clinical medical physics Aug 26, 2024
PURPOSE: To develop a non-coplanar cone-beam computed tomography (CBCT) image reconstruction method using projections within a limited angle range for non-coplanar radiotherapy.
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Phantoms, Imaging Radiotherapy, Image-Guided Brain Neoplasms Cone-Beam Computed Tomography Image Processing, Computer-Assisted Organs at Risk Humans Neural Networks, Computer Algorithms
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Dual-branch Transformer for semi-supervised medical image segmentation.

Journal of applied clinical medical physics Aug 12, 2024
PURPOSE: In recent years, the use of deep learning for medical image segmentation has become a popular trend, but its development also faces some challenges. Firstly, due to the specialized nature of medical data, precise annotation is time-consuming...
SARS-CoV-2 Deep Learning Image Processing, Computer-Assisted Supervised Machine Learning COVID-19 Algorithms Tomography, X-Ray Computed Humans Neural Networks, Computer
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Deep learning based clinical target volumes contouring for prostate cancer: Easy and efficient application.

Journal of applied clinical medical physics Aug 9, 2024
BACKGROUND: Radiotherapy has been crucial in prostate cancer treatment. However, manual segmentation is labor intensive and highly variable among radiation oncologists. In this study, a deep learning based automated contouring model is constructed fo...
Tomography, X-Ray Computed Aged Male Middle Aged Humans Algorithms Prognosis Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Deep Learning Image Processing, Computer-Assisted Prostatic Neoplasms
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A quantitative analysis of the improvement provided by comprehensive annotation on CT lesion detection using deep learning.

Journal of applied clinical medical physics Jul 30, 2024
BACKGROUND: Data collected from hospitals are usually partially annotated by radiologists due to time constraints. Developing and evaluating deep learning models on these data may result in over or under estimation PURPOSE: We aimed to quantitatively...
Humans Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Neoplasms Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Databases, Factual
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Machine learning-based estimation of patient body weight from radiation dose metrics in computed tomography.

Journal of applied clinical medical physics Jul 23, 2024
PURPOSE: Currently, precise patient body weight (BW) at the time of diagnostic imaging cannot always be used for radiation dose management. Various methods have been explored to address this issue, including the application of deep learning to medica...
Humans Machine Learning Algorithms Tomography, X-Ray Computed Female Aged Image Processing, Computer-Assisted Body Weight Radiation Dosage Adult Male Middle Aged
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From plan to delivery: Machine learning based positional accuracy prediction of multi-leaf collimator and estimation of delivery effect in volumetric modulated arc therapy.

Journal of applied clinical medical physics Jun 20, 2024
PURPOSE: The positional accuracy of MLC is an important element in establishing the exact dosimetry in VMAT. We comprehensively analyzed factors that may affect MLC positional accuracy in VMAT, and constructed a model to predict MLC positional deviat...
Humans Radiotherapy Dosage Machine Learning Neoplasms Radiotherapy, Intensity-Modulated Algorithms Particle Accelerators Organs at Risk Radiotherapy Planning, Computer-Assisted
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Clinical evaluation of deep learning-enhanced lymphoma pet imaging with accelerated acquisition.

Journal of applied clinical medical physics May 29, 2024
PURPOSE: This study aims to evaluate the clinical performance of a deep learning (DL)-enhanced two-fold accelerated PET imaging method in patients with lymphoma.
Whole Body Imaging Image Interpretation, Computer-Assisted Fluorodeoxyglucose F18 Signal-To-Noise Ratio Male Image Processing, Computer-Assisted Aged Lymphoma Humans Aged, 80 and over Positron Emission Tomography Computed Tomography Prognosis Young Adult Radiopharmaceuticals Female Adult Middle Aged Deep Learning
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