AIMC Journal:
Medical physics

Showing 231 to 240 of 732 articles

Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

Medical physics Jan 6, 2023
BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell lung cancer (NSCLC) before surgery is crucial, while there is lack of corresponding method clinically.
Humans Retrospective Studies Carcinoma, Non-Small-Cell Lung Lymphatic Metastasis Carcinoma Deep Learning Lung Neoplasms
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AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging.

Medical physics Jan 6, 2023
Rapid advances in artificial intelligence (AI) and machine learning, and specifically in deep learning (DL) techniques, have enabled broad application of these methods in health care. The promise of the DL approach has spurred further interest in com...
Diagnosis, Computer-Assisted Diagnostic Imaging Humans Machine Learning Reproducibility of Results Artificial Intelligence
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Technical performance of a dual-energy CT system with a novel deep-learning based reconstruction process: Evaluation using an abdomen protocol.

Medical physics Dec 29, 2022
BACKGROUND: A new tube voltage-switching dual-energy (DE) CT system using a novel deep-learning based reconstruction process has been introduced. Characterizing the performance of this DE approach can help demonstrate its benefits and potential drawb...
Polyethylene Tomography, X-Ray Computed Iodine Phantoms, Imaging Deep Learning Abdomen
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Abdomen CT multi-organ segmentation using token-based MLP-Mixer.

Medical physics Dec 20, 2022
BACKGROUND: Manual contouring is very labor-intensive, time-consuming, and subject to intra- and inter-observer variability. An automated deep learning approach to fast and accurate contouring and segmentation is desirable during radiotherapy treatme...
Lung Image Processing, Computer-Assisted Algorithms Tomography, X-Ray Computed Abdomen Humans Neural Networks, Computer
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Ensemble learning and personalized training for the improvement of unsupervised deep learning-based synthetic CT reconstruction.

Medical physics Dec 17, 2022
BACKGROUND: The growing adoption of magnetic resonance imaging (MRI)-guided radiation therapy (RT) platforms and a focus on MRI-only RT workflows have brought the technical challenge of synthetic computed tomography (sCT) reconstruction to the forefr...
Humans Radiotherapy, Image-Guided Image Processing, Computer-Assisted Tomography, X-Ray Computed Magnetic Resonance Imaging Deep Learning
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Deep learning-based motion quantification from k-space for fast model-based magnetic resonance imaging motion correction.

Medical physics Dec 13, 2022
BACKGROUND: Intra-scan rigid-body motion is a costly and ubiquitous problem in clinical magnetic resonance imaging (MRI) of the head.
Deep Learning Image Processing, Computer-Assisted Motion Artifacts Retrospective Studies Magnetic Resonance Imaging
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A multi-scale, multi-region and attention mechanism-based deep learning framework for prediction of grading in hepatocellular carcinoma.

Medical physics Dec 10, 2022
BACKGROUND: Histopathological grading is a significant risk factor for postsurgical recurrence in hepatocellular carcinoma (HCC). Preoperative knowledge of histopathological grading could provide instructive guidance for individualized treatment deci...
Carcinoma, Hepatocellular Retrospective Studies Deep Learning Liver Neoplasms Humans Risk Factors Tumor Microenvironment
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Fully automated cardiac MRI segmentation using dilated residual network.

Medical physics Dec 7, 2022
PURPOSE: Cardiac ventricle segmentation from cine magnetic resonance imaging (CMRI) is a recognized modality for the noninvasive assessment of cardiovascular pathologies. Deep learning based algorithms achieved state-of-the-art result performance fro...
Humans Neural Networks, Computer Heart Heart Ventricles Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Deep learning architecture with transformer and semantic field alignment for voxel-level dose prediction on brain tumors.

Medical physics Dec 5, 2022
PURPOSE: The use of convolution neural networks (CNN) to accurately predict dose distributions can accelerate intensity-modulated radiation therapy (IMRT) planning. The purpose of our study is to develop a novel deep learning architecture for precise...
Retrospective Studies Brain Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Deep Learning Humans Radiotherapy, Intensity-Modulated Semantics Radiotherapy Dosage
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Deep learning-based motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) reconstruction.

Medical physics Dec 3, 2022
BACKGROUND: Motion-compensated (MoCo) reconstruction shows great promise in improving four-dimensional cone-beam computed tomography (4D-CBCT) image quality. MoCo reconstruction for a 4D-CBCT could be more accurate using motion information at the CBC...
Four-Dimensional Computed Tomography Spiral Cone-Beam Computed Tomography Image Processing, Computer-Assisted Lung Neoplasms Motion Phantoms, Imaging Deep Learning Cone-Beam Computed Tomography Humans Algorithms
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