PURPOSE: To develop and evaluate a method to automatically identify and quantify deformable image registration (DIR) errors between lung computed tomography (CT) scans for quality assurance (QA) purposes.
PURPOSE: Deep neural network-based image reconstruction has demonstrated promising performance in medical imaging for undersampled and low-dose scenarios. However, it requires large amount of memory and extensive time for the training. It is especial...
European journal of nuclear medicine and molecular imaging
Aug 29, 2019
PURPOSE: Image quality of positron emission tomography (PET) is limited by various physical degradation factors. Our study aims to perform PET image denoising by utilizing prior information from the same patient. The proposed method is based on unsup...
PURPOSE: Intensity-modulated radiation therapy (IMRT) quality assurance (QA) measurements are routinely performed prior to treatment delivery to verify dose calculation and delivery accuracy. In this work, we applied a machine learning-based approach...
Medical & biological engineering & computing
Aug 24, 2019
The objective of this work is to reduce the user effort required for 2D segmentation when building patient-specific cardiovascular models using the SimVascular cardiovascular modeling software package. The proposed method uses a fully convolutional n...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Aug 17, 2019
INTRODUCTION: Breathing artifact may affect the quality of four-dimensional computed tomography (4DCT) images. We developed a deep neural network (DNN)-based artifact reduction method.
As the airline industry has become ever-more competitive and profitability more tenuous, airline service quality management has grown more important to airlines. Although many studies have focused on the evaluation of airline service quality, some co...
OBJECTIVE: The accuracy of dose delivery for intensity modulated radiotherapy (IMRT) treatments should be determined by an accurate quality assurance procedure. In this work, we used artificial neural networks (ANNs) as an application for the pre-tre...
OBJECTIVES: This study sought to develop a fully automated framework for cardiac function analysis from cardiac magnetic resonance (CMR), including comprehensive quality control (QC) algorithms to detect erroneous output.
Journal of the American College of Radiology : JACR
Jun 26, 2019
The advent of artificial intelligence (AI) promises to have a transformational impact on quality in medicine, including in radiology. However, experience has shown that quality tools alone are often not sufficient to bring about consistent excellent ...