Esophagus : official journal of the Japan Esophageal Society
Feb 26, 2021
BACKGROUND: Because cancers of hollow organs such as the esophagus are hard to detect even by the expert physician, it is important to establish diagnostic systems to support physicians and increase the accuracy of diagnosis. In recent years, deep le...
OBJECTIVE: This study aims to investigate the safety and feasibility of using a deep learning algorithm to calculate computed tomography angiography-based fractional flow reserve (DL-FFRCT) as an alternative to invasive coronary angiography (ICA) in ...
OBJECTIVES: To reduce the dose of intravenous iodine-based contrast media (ICM) in CT through virtual contrast-enhanced images using generative adversarial networks.
OBJECTIVE: To compare the performance of the deep learning-based lesion detection algorithm (DLLD) in detecting liver metastasis with that of radiologists.
BACKGROUND: In breast cancer patients receiving radiotherapy (RT), accurate target delineation and reduction of radiation doses to the nearby normal organs is important. However, manual clinical target volume (CTV) and organs-at-risk (OARs) segmentat...
OBJECTIVE: The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) has caused more than 26 million cases of Corona virus disease (COVID-19) in the world so far. To control the spread of the disease, screening large numbers of sus...
OBJECTIVE: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management.
Clinical cancer research : an official journal of the American Association for Cancer Research
Feb 24, 2021
PURPOSE: Nodule evaluation is challenging and critical to diagnose multiple pulmonary nodules (MPNs). We aimed to develop and validate a machine learning-based model to estimate the malignant probability of MPNs to guide decision-making.
OBJECTIVES: To compare the image quality of low-dose CT urography (LD-CTU) using deep learning image reconstruction (DLIR) with conventional CTU (C-CTU) using adaptive statistical iterative reconstruction (ASIR-V).
Biomedical physics & engineering express
Feb 24, 2021
Replacing CT imaging with MR imaging for MR-only radiotherapy has sparked the interest of many scientists and is being increasingly adopted in radiation oncology. Although many studies have focused on generating CT images from MR images, only models ...
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