AIMC Topic: Organs at Risk

Clear Filters Showing 71 to 80 of 326 articles

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...
Humans Neoplasms Radiotherapy Dosage Artificial Intelligence Radiotherapy, Intensity-Modulated Organs at Risk Algorithms Radiotherapy Planning, Computer-Assisted Movement
View on PubMed DOI

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 Humans Radiotherapy, Image-Guided Cone-Beam Computed Tomography Image Processing, Computer-Assisted Neural Networks, Computer Organs at Risk Algorithms Brain Neoplasms
View on PubMed DOI

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...
Humans Neural Networks, Computer Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Tomography, X-Ray Computed Deep Learning Liver Neoplasms
View on PubMed DOI

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.
Radiotherapy, Image-Guided Radiotherapy Planning, Computer-Assisted Brachytherapy Urinary Bladder Rectum Colon, Sigmoid Organs at Risk Humans Neural Networks, Computer Tomography, X-Ray Computed Uterine Cervical Neoplasms Female Middle Aged Adult
View on PubMed DOI

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 ...
Head and Neck Neoplasms Organs at Risk Probability Male Middle Aged Deep Learning Xerostomia Radiotherapy Dosage Radiation Injuries Salivary Glands Humans Tomography, X-Ray Computed Aged, 80 and over Adult Female Aged
View on PubMed DOI

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...
Humans Algorithms Prognosis Prostatic Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Tomography, X-Ray Computed Radiotherapy Dosage Radiotherapy, Intensity-Modulated Middle Aged Aged Deep Learning Male Image Processing, Computer-Assisted
View on PubMed DOI

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...
Radiotherapy Planning, Computer-Assisted Tumor Burden Deep Learning Humans Radiation Oncology Neoplasms Organs at Risk
View on PubMed DOI

Clinical implementation and evaluation of deep learning-assisted automatic radiotherapy treatment planning for lung cancer.

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) Aug 2, 2024
PURPOSE: The purpose of the study is to investigate the clinical application of deep learning (DL)-assisted automatic radiotherapy planning for lung cancer.
Humans Retrospective Studies Radiotherapy Planning, Computer-Assisted Automation Radiotherapy Dosage Radiotherapy, Intensity-Modulated Deep Learning Lung Neoplasms Organs at Risk
View on PubMed DOI

Deep-learning-based segmentation using individual patient data on prostate cancer radiation therapy.

PloS one Jul 31, 2024
PURPOSE: Organ-at-risk segmentation is essential in adaptive radiotherapy (ART). Learning-based automatic segmentation can reduce committed labor and accelerate the ART process. In this study, an auto-segmentation model was developed by employing ind...
Deep Learning Urinary Bladder Prostate Humans Image Processing, Computer-Assisted Tomography, X-Ray Computed Organs at Risk Prostatic Neoplasms Male Radiotherapy Planning, Computer-Assisted
View on PubMed DOI

Deep learning-based voxel sampling for particle therapy treatment planning.

Physics in medicine and biology Jul 19, 2024
Scanned particle therapy often requires complex treatment plans, robust optimization, as well as treatment adaptation. Plan optimization is especially complicated for heavy ions due to the variable relative biological effectiveness. We present a nove...
Organs at Risk Deep Learning Radiotherapy Planning, Computer-Assisted Humans Heavy Ion Radiotherapy Head and Neck Neoplasms
View on PubMed DOI
Popular Topics
Recent Journals