| Deep learning in medical imaging and radiation therapy |
87 |
| Tolerance limits and methodologies for IMRT measurement-based verification QA: Recommendations of AAPM Task Group No. 218 |
75 |
| Geant4-DNA example applications for track structure simulations in liquid water: A report from the Geant4-DNA Project |
49 |
| AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy |
49 |
| Automatic multiorgan segmentation in thorax CT images using U-net-GAN |
46 |
| Deeply supervised 3D fully convolutional networks with group dilated convolution for automatic MRI prostate segmentation |
44 |
| Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers |
36 |
| Generating synthetic CTs from magnetic resonance images using generative adversarial networks |
34 |
| Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique |
34 |
| A deep learning method for classifying mammographic breast density categories |
34 |
| Recent advances on the development of phantoms using 3D printing for imaging with CT, MRI, PET, SPECT, and ultrasound |
33 |
| RECORDS: improved Reporting of montE CarlO RaDiation transport Studies: Report of the AAPM Research Committee Task Group 268 |
33 |
| Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks |
30 |
| MRI-only based synthetic CT generation using dense cycle consistent generative adversarial networks |
29 |
| Paired cycle-GAN-based image correction for quantitative cone-beam computed tomography |
28 |
| High dose-per-pulse electron beam dosimetry: Commissioning of the Oriatron eRT6 prototype linear accelerator for preclinical use |
27 |
| Breast mass classification in sonography with transfer learning using a deep convolutional neural network and color conversion |
27 |
| Ultrasound prostate segmentation based on multidirectional deeply supervised V-Net |
26 |
| In vivo range verification in particle therapy |
25 |
| A novel MRI segmentation method using CNN-based correction network for MRI-guided adaptive radiotherapy |
25 |
| Cycle-consistent adversarial denoising network for multiphase coronary CT angiography |
24 |
| First clinical implementation of real-time, real anatomy tracking and radiation beam control |
23 |
| Dosimetry of small static fields used in external photon beam radiotherapy: Summary of TRS- the IAEA-AAPM international Code of Practice for reference and relative dose determination |
23 |
| Breast cancer MRI radiomics: An overview of algorithmic features and impact of inter-reader variability in annotating tumors |
22 |
| Three-dimensional dose prediction for lung IMRT patients with deep neural networks: robust learning from heterogeneous beam configurations |
20 |
| Interleaved 3D-CNNs for joint segmentation of small-volume structures in head and neck CT images |
20 |
| Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017 |
19 |
| Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation |
18 |
| Radiomics analysis of pulmonary nodules in low-dose CT for early detection of lung cancer |
18 |
| Performance evaluation of the 5-Ring GE Discovery MI PET/CT system using the national electrical manufacturers association NU 2-2012 Standard |
18 |
| Performance evaluation of computed tomography systems: Summary of AAPM Task Group 233 |
18 |
| ScatterNet: A convolutional neural network for cone-beam CT intensity correction |
18 |
| CT radiomics to predict high-risk intraductal papillary mucinous neoplasms of the pancreas |
17 |
| Performance of commercially available deformable image registration platforms for contour propagation using patient-based computational phantoms: A multi-institutional study |
17 |
| Knowledge-based planning for intensity-modulated radiation therapy: A review of data-driven approaches |
17 |
| A feasibility study on an automated method to generate patient-specific dose distributions for radiotherapy using deep learning |
16 |
| Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region |
16 |
| Learning-based automatic segmentation of arteriovenous malformations on contrast CT images in brain stereotactic radiosurgery |
16 |
| Technical Note: Extension of CERR for computational radiomics: A comprehensive MATLAB platform for reproducible radiomics research |
16 |
| Patient-specific validation of deformable image registration in radiation therapy: Overview and caveats |
16 |
| Radiobiological issues in prospective carbon ion therapy trials |
16 |
| Image guidance doses delivered during radiotherapy: Quantification, management, and reduction: Report of the AAPM Therapy Physics Committee Task Group 180 |
15 |
| Deep learning for segmentation of brain tumors: Impact of cross-institutional training and testing |
15 |
| A deep learning-based prediction model for gamma evaluation in patient-specific quality assurance |
15 |
| A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection |
15 |
| Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging |
15 |
| Knowledge-based automated planning for oropharyngeal cancer |
15 |
| Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss |
15 |
| Deep convolutional neural network for segmentation of thoracic organs-at-risk using cropped 3D images |
15 |
| Deep learning for patient-specific quality assurance: Identifying errors in radiotherapy delivery by radiomic analysis of gamma images with convolutional neural networks |
14 |
