AIMC Topic: Organs at Risk

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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.
Humans Software Algorithms Prognosis Radiotherapy Planning, Computer-Assisted Deep Learning Radiotherapy Dosage Head and Neck Neoplasms Radiotherapy, Intensity-Modulated 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...
Radiotherapy, Intensity-Modulated Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Algorithms Retrospective Studies Deep Learning Brain Neoplasms Image Processing, Computer-Assisted Humans Glioma Magnetic Resonance Imaging
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Deep learning method for predicting weekly anatomical changes in patients with nasopharyngeal carcinoma during radiotherapy.

Medical physics Sep 3, 2024
BACKGROUND: Patients may undergo anatomical changes during radiotherapy, leading to an underdosing of the target or overdosing of the organs at risk (OARs).
Humans Deep Learning Time Factors Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Cone-Beam Computed Tomography Nasopharyngeal Carcinoma Image Processing, Computer-Assisted Nasopharyngeal Neoplasms Organs at Risk
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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...
Radiotherapy, Intensity-Modulated Neoplasms Movement Humans Organs at Risk Artificial Intelligence Radiotherapy Planning, Computer-Assisted Algorithms Radiotherapy Dosage
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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 Dosage Humans Radiotherapy, Intensity-Modulated Image Processing, Computer-Assisted Phantoms, Imaging Neural Networks, Computer Organs at Risk Radiotherapy, Image-Guided Algorithms Radiotherapy Planning, Computer-Assisted Brain Neoplasms Cone-Beam Computed Tomography
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FA-Net: A hierarchical feature fusion and interactive attention-based network for dose prediction in liver cancer patients.

Artificial intelligence in medicine Aug 18, 2024
Dose prediction is a crucial step in automated radiotherapy planning for liver cancer. Several deep learning-based approaches for dose prediction have been proposed to enhance the design efficiency and quality of radiotherapy plan. However, these app...
Radiotherapy Dosage Deep Learning Humans Liver Neoplasms Neural Networks, Computer Organs at Risk Tomography, X-Ray Computed Radiotherapy Planning, Computer-Assisted
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Automatic segmentation of high-risk clinical target volume and organs at risk in brachytherapy of cervical cancer with a convolutional neural network.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique Aug 14, 2024
PURPOSE: This study aimed to design an autodelineation model based on convolutional neural networks for generating high-risk clinical target volumes and organs at risk in image-guided adaptive brachytherapy for cervical cancer.
Middle Aged Rectum Colon, Sigmoid Organs at Risk Radiotherapy Planning, Computer-Assisted Brachytherapy Urinary Bladder Tomography, X-Ray Computed Female Adult Uterine Cervical Neoplasms Humans Neural Networks, Computer Radiotherapy, Image-Guided
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Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck Cancer.

International journal of radiation oncology, biology, physics Aug 13, 2024
PURPOSE: Conventional normal tissue complication probability (NTCP) models for patients with head and neck cancer are typically based on single-value variables, which, for radiation-induced xerostomia, are baseline xerostomia and mean salivary gland ...
Radiation Injuries Salivary Glands Xerostomia Male Middle Aged Deep Learning Head and Neck Neoplasms Organs at Risk Probability Female Radiotherapy Dosage Humans Aged Tomography, X-Ray Computed Aged, 80 and over Adult
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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...
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Aged Male Middle Aged Deep Learning Image Processing, Computer-Assisted Prostatic Neoplasms Organs at Risk Humans Algorithms Prognosis Tomography, X-Ray Computed
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Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] Aug 6, 2024
The rapid development of artificial intelligence (AI) has gained importance, with many tools already entering our daily lives. The medical field of radiation oncology is also subject to this development, with AI entering all steps of the patient jour...
Humans Neoplasms Deep Learning Radiation Oncology Organs at Risk Radiotherapy Planning, Computer-Assisted Tumor Burden
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