AIMC Topic: Radiotherapy, Image-Guided
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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.
Artificial intelligence for treatment delivery: image-guided radiotherapy.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Aug 13, 2024
Radiation therapy (RT) is a highly digitized field relying heavily on computational methods and, as such, has a high affinity for the automation potential afforded by modern artificial intelligence (AI). This is particularly relevant where imaging is...
Deep learning-based dose prediction for magnetic resonance-guided prostate radiotherapy.
Medical physics
Aug 6, 2024
BACKGROUND: Daily adaptive radiotherapy, as performed with the Elekta Unity MR-Linac, requires choosing between different adaptation methods, namely ATP (Adapt to Position) and ATS (Adapt to Shape), where the latter requires daily re-contouring to ob...
Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic resonance only radiotherapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jun 15, 2024
Synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI) can serve as a substitute for planning CT in radiation therapy (RT), thereby removing registration uncertainties associated with multi-modality imaging pairing, reduc...
Re-evaluation of the prospective risk analysis for artificial-intelligence driven cone beam computed tomography-based online adaptive radiotherapy after one year of clinical experience.
Zeitschrift fur medizinische Physik
Jun 8, 2024
Cone-beam computed tomography (CBCT)-based online adaptation is increasingly being introduced into many clinics. Upon implementation of a new treatment technique, a prospective risk analysis is required and enhances workflow safety. We conducted a ri...
Enhancing Precision in Cardiac Segmentation for Magnetic Resonance-Guided Radiation Therapy Through Deep Learning.
International journal of radiation oncology, biology, physics
May 24, 2024
PURPOSE: Cardiac substructure dose metrics are more strongly linked to late cardiac morbidities than to whole-heart metrics. Magnetic resonance (MR)-guided radiation therapy (MRgRT) enables substructure visualization during daily localization, allowi...
Generalizability of deep learning in organ-at-risk segmentation: A transfer learning study in cervical brachytherapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
May 18, 2024
PURPOSE: Deep learning can automate delineation in radiation therapy, reducing time and variability. Yet, its efficacy varies across different institutions, scanners, or settings, emphasizing the need for adaptable and robust models in clinical envir...
Rapid multi-catheter segmentation for magnetic resonance image-guided catheter-based interventions.
Medical physics
May 7, 2024
BACKGROUND: Magnetic resonance imaging (MRI) is the gold standard for delineating cancerous lesions in soft tissue. Catheter-based interventions require the accurate placement of multiple long, flexible catheters at the target site. The manual segmen...
Assessment of the deep learning-based gamma passing rate prediction system for 1.5 T magnetic resonance-guided linear accelerator.
Radiological physics and technology
Apr 30, 2024
Measurement-based verification is impossible for the patient-specific quality assurance (QA) of online adaptive magnetic resonance imaging-guided radiotherapy (oMRgRT) because the patient remains on the couch throughout the session. We assessed a dee...
Deep learning-based target decomposition for markerless lung tumor tracking in radiotherapy.
Medical physics
Mar 20, 2024
BACKGROUND: In radiotherapy, real-time tumor tracking can verify tumor position during beam delivery, guide the radiation beam to target the tumor, and reduce the chance of a geometric miss. Markerless kV x-ray image-based tumor tracking is challengi...
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