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High‐fidelity fast volumetric brain MRI using synergistic wave‐controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN)
High‐fidelity fast volumetric brain MRI using synergistic wave‐controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN)
Abstract Purpose : The goal of this study is to leverage an advanced fast imaging technique, wave-controlled aliasing in p...
Performance of a deep learning‐based CT image denoising method: Generalizability over dose, reconstruction kernel and slice thickness
Performance of a deep learning‐based CT image denoising method: Generalizability over dose, reconstruction kernel and slice thickness
Abstract Purpose : Deep learning (DL) is rapidly finding applications in low-dose CT image denoising. While having the pot...
Monte Carlo evaluation of hypothetical long axial field‐of‐view PET scanner using GE discovery MI PET front‐end architecture
Monte Carlo evaluation of hypothetical long axial field‐of‐view PET scanner using GE discovery MI PET front‐end architecture
Abstract Purpose The development of total-body PET scanners is of growing interest in the PET community. Investigation int...
Assessment of breast cancer response to neoadjuvant chemotherapy based on ultrasound backscattering envelope statistics
Assessment of breast cancer response to neoadjuvant chemotherapy based on ultrasound backscattering envelope statistics
Abstract Purpose Neoadjuvant chemotherapy (NAC) is used in breast cancer before tumor surgery to reduce the size of the tu...
Assessing the accuracy of electronic portal imaging device (EPID)‐based dosimetry: II. Evaluation of a dosimetric uncertainty budget and development of a new film‐in‐EPID absorbed dose calibration methodology
Assessing the accuracy of electronic portal imaging device (EPID)‐based dosimetry: II. Evaluation of a dosimetric uncertainty budget and development of a new film‐in‐EPID absorbed dose calibration methodology
Abstract Purpose : The aim of this study is to reduce the uncertainty associated with determining dose-to-water using an a...
Edge‐Enhancement DenseNet for X‐ray Fluoroscopy Image Denoising in Cardiac Electrophysiology Procedures
Edge‐Enhancement DenseNet for X‐ray Fluoroscopy Image Denoising in Cardiac Electrophysiology Procedures
Abstract Purpose Reducing X-ray dose increases safety in cardiac electrophysiology procedures but also increases image noi...
Multi‐level multi‐leaf collimators: optimization of layer thicknesses and a feasibility study
Multi‐level multi‐leaf collimators: optimization of layer thicknesses and a feasibility study
Abstract Purpose : The function of multi-leaf collimators (MLC) is to modulate and shape the intensity of a radiotherapy b...
Automated 3D U‐net based segmentation of neonatal cerebral ventricles from 3D ultrasound images
Automated 3D U‐net based segmentation of neonatal cerebral ventricles from 3D ultrasound images
Abstract Background : Intraventricular hemorrhaging (IVH) within cerebral lateral ventricles affects 20–30% of very...
Optical imaging of lithium‐containing zinc sulfate plate in water during irradiation of neutrons from boron neutron capture therapy (BNCT) system
Optical imaging of lithium‐containing zinc sulfate plate in water during irradiation of neutrons from boron neutron capture therapy (BNCT) system
Abstract Purpose : Optical imaging of ionizing radiation is a possible method for dose distribution measurements. However,...
TransDIR: Deformable imaging registration network based on transformer to improve the feature extraction ability
TransDIR: Deformable imaging registration network based on transformer to improve the feature extraction ability
Abstract Purpose Imaging registration have a significant contribution to guide and support physicians in the process of de...
Automatic COVID‐19 diagnosis based on chest radiography and deep learning – success story or dataset bias?
Automatic COVID‐19 diagnosis based on chest radiography and deep learning – success story or dataset bias?
Abstract Purpose Over the last two years, the artificial intelligence (AI) community has presented several automatic scree...
Performance evaluation of dual‐energy CT and differential phase contrast CT in quantitative imaging applications
Performance evaluation of dual‐energy CT and differential phase contrast CT in quantitative imaging applications
Abstract Purpose The purpose of this study is to evaluate and compare the quantitative material decomposition performance ...
Volumetric segmentation of ground glass nodule based on 3D attentional cascaded residual U‐net and conditional radom field
Volumetric segmentation of ground glass nodule based on 3D attentional cascaded residual U‐net and conditional radom field
Abstract Background : Ground glass nodule (GGN) segmentation is one of the important and challenging tasks in diagnosing e...
DblurDoseNet: A deep residual learning network for voxel radionuclide dosimetry compensating for single‐photon emission computerized tomography imaging resolution
DblurDoseNet: A deep residual learning network for voxel radionuclide dosimetry compensating for single‐photon emission computerized tomography imaging resolution
Abstract Purpose Current methods for patient-specific voxel-level dosimetry in radionuclide therapy suffer from a trade-of...
A GPU‐accelerated framework for individualized estimation of organ doses in digital tomosynthesis
A GPU‐accelerated framework for individualized estimation of organ doses in digital tomosynthesis
Abstract Purpose Estimation of organ doses in digital tomosynthesis (DT) is challenging due to the lack of existing tools ...
Advancing size‐specific dose estimates in CT examinations: Dose estimates at longitudinal positions of scans
Advancing size‐specific dose estimates in CT examinations: Dose estimates at longitudinal positions of scans
Purpose American Association of Physicists in Medicine (AAPM) (Report 204) introduced the size-specific dose estimate (SSD...
Convolution neural network toward Monte Carlo photon dose calculation in radiation therapy
Convolution neural network toward Monte Carlo photon dose calculation in radiation therapy
Abstract Purpose The Monte Carlo (MC) algorithm has been widely accepted as the most accurate algorithm for dosimetric cal...
The effect of image annotation with minimal manual interaction for semiautomatic prostate segmentation in CT images using fully convolutional neural networks
The effect of image annotation with minimal manual interaction for semiautomatic prostate segmentation in CT images using fully convolutional neural networks
Abstract Purpose The goal is to study the performance improvement of a deep learning algorithm in three-dimensional (3D) i...
Technical Note: 3D printed phantom for dedicated cardiac protocols and geometries in nuclear medicine
Technical Note: 3D printed phantom for dedicated cardiac protocols and geometries in nuclear medicine
Abstract Purpose The purpose of this study was to create and validate a 3D-printed nuclear cardiac phantom for low cost, u...
Three‐dimensional printing of patient‐specific lung phantoms for CT imaging: emulating lung tissue with accurate attenuation profiles and textures
Three‐dimensional printing of patient‐specific lung phantoms for CT imaging: emulating lung tissue with accurate attenuation profiles and textures
Abstract Purpose Phantoms are a basic tool for assessing and verifying performance in CT research and clinical practice. P...
The markerless lung target tracking AAPM grand challenge (MATCH) results
The markerless lung target tracking AAPM grand challenge (MATCH) results
Abstract Purpose Lung stereotactic ablative body radiotherapy (SABR) is a radiation therapy success story with level 1 evi...
Photon‐counting CT via interleaved/gapped spectral channels: Feasibility and imaging performance
Photon‐counting CT via interleaved/gapped spectral channels: Feasibility and imaging performance
Abstract Purpose Compared to energy-integration, photon-counting x-ray detection facilitates the spectral channelization (...
Technical Note: Does the greater power of pencil beam scanning reduce the need for a proton gantry? A study of head‐and‐neck and brain tumors
Technical Note: Does the greater power of pencil beam scanning reduce the need for a proton gantry? A study of head‐and‐neck and brain tumors
Abstract Purpose Proton therapy systems without a gantry can be more compact and less expensive in terms of capital cost, ...
Commissioning and routine quality assurance of the radixact synchrony system
Commissioning and routine quality assurance of the radixact synchrony system
Abstract Purpose The Radixact Synchrony system allows for target motion correction when tracking either fiducials in/aroun...
Dynamic boundary‐insensitive loss for magnetic resonance medical image segmentation
Dynamic boundary‐insensitive loss for magnetic resonance medical image segmentation
Abstract Purpose A deep learning method has achieved great success in MR medical image segmentation. One challenge in appl...
Convolution neural network towards Monte Carlo photon dose calculation in radiation therapy
Convolution neural network towards Monte Carlo photon dose calculation in radiation therapy
Abstract Purpose The Monte Carlo (MC) algorithm has been widely accepted as the most accurate algorithm for dosimetric cal...
Normal tissue complication probability modeling to guide individual treatment planning in pediatric cranial proton and photon radiotherapy
Normal tissue complication probability modeling to guide individual treatment planning in pediatric cranial proton and photon radiotherapy
Abstract Purpose Proton therapy (PT) is broadly accepted as the gold standard of care for pediatric patients with cranial ...
Synthesizing high‐resolution magnetic resonance imaging using parallel cycle‐consistent generative adversarial networks for fast magnetic resonance imaging
Synthesizing high‐resolution magnetic resonance imaging using parallel cycle‐consistent generative adversarial networks for fast magnetic resonance imaging
Abstract Purpose The common practice in acquiring the magnetic resonance (MR) images is to obtain two-dimensional (2D) sli...
A GPU‐accelerated framework for individualized estimation of organ dose in digital tomosynthesis
A GPU‐accelerated framework for individualized estimation of organ dose in digital tomosynthesis
ABSTRACT Purpose Estimation of organ dose in digital tomosynthesis (DT) is challenging due to the lack of existing tools t...
Texture and shape analysis of diffusion‐weighted imaging for thyroid nodules classification using machine learning
Texture and shape analysis of diffusion‐weighted imaging for thyroid nodules classification using machine learning
Abstract Purpose To assess whether the integration between (a) functional imaging features that will be extracted from Dif...
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