AIMC Topic: Abdominal Neoplasms
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Personalized deep learning auto-segmentation models for adaptive fractionated magnetic resonance-guided radiation therapy of the abdomen.
Medical physics
Dec 19, 2024
BACKGROUND: Manual contour corrections during fractionated magnetic resonance (MR)-guided radiotherapy (MRgRT) are time-consuming. Conventional population models for deep learning auto-segmentation might be suboptimal for MRgRT at MR-Linacs since the...
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.
Humans
Feasibility Studies
Phantoms, Imaging
Organs at Risk
Abdominal Neoplasms
Male
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Image-Guided
Deep Learning
Signal-To-Noise Ratio
Radiation Dosage
Radiographic Image Enhancement
Image Processing, Computer-Assisted
Pelvic Neoplasms
Algorithms
Radiographic Image Interpretation, Computer-Assisted
Radiotherapy Dosage
Prospective Studies
Radiotherapy, Intensity-Modulated
Tomography, X-Ray Computed
Female
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...
Automated deep learning auto-segmentation of air volumes for MRI-guided online adaptive radiation therapy of abdominal tumors.
Physics in medicine and biology
Jun 15, 2023
. In the current MR-Linac online adaptive workflow, air regions on the MR images need to be manually delineated for abdominal targets, and then overridden by air density for dose calculation. Auto-delineation of these regions is desirable for speed p...
Deep-learning-based image reconstruction in dynamic contrast-enhanced abdominal CT: image quality and lesion detection among reconstruction strength levels.
Clinical radiology
Apr 18, 2021
AIM: To evaluate the use of deep-learning-based image reconstruction (DLIR) algorithms in dynamic contrast-enhanced computed tomography (CT) of the abdomen, and to compare the image quality and lesion conspicuity among the reconstruction strength lev...
DeepDose: a robust deep learning-based dose engine for abdominal tumours in a 1.5 T MRI radiotherapy system.
Physics in medicine and biology
Mar 9, 2021
We present a robust deep learning-based framework for dose calculations of abdominal tumours in a 1.5 T MRI radiotherapy system. For a set of patient plans, a convolutional neural network is trained on the dose of individual multi-leaf-collimator seg...
Humans
Neural Networks, Computer
Reproducibility of Results
Radiotherapy, Intensity-Modulated
Rectal Neoplasms
Male
Radiotherapy Planning, Computer-Assisted
Deep Learning
Monte Carlo Method
Neoplasm Metastasis
Magnetic Resonance Imaging
Abdominal Neoplasms
Radiotherapy Dosage
Prostatic Neoplasms
Particle Accelerators
Deep learning prediction of proton and photon dose distributions for paediatric abdominal tumours.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Nov 29, 2020
OBJECTIVE: Dose prediction using deep learning networks prior to radiotherapy might lead tomore efficient modality selections. The study goal was to predict proton and photon dose distributions based on the patient-specific anatomy and to assess thei...
Deep learning-enabled MRI-only photon and proton therapy treatment planning for paediatric abdominal tumours.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Oct 7, 2020
PURPOSE: To assess the feasibility of magnetic resonance imaging (MRI)-only treatment planning for photon and proton radiotherapy in children with abdominal tumours.
Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy.
Physics in medicine and biology
Aug 7, 2020
To enable magnetic resonance imaging (MRI)-guided radiotherapy with real-time adaptation, motion must be quickly estimated with low latency. The motion estimate is used to adapt the radiation beam to the current anatomy, yielding a more conformal dos...
A convolutional neural network-based system to classify patients using FDG PET/CT examinations.
BMC cancer
Mar 17, 2020
BACKGROUND: As the number of PET/CT scanners increases and FDG PET/CT becomes a common imaging modality for oncology, the demands for automated detection systems on artificial intelligence (AI) to prevent human oversight and misdiagnosis are rapidly ...
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