The success of deep learning in recent years has arguably been driven by the availability of large datasets for training powerful predictive algorithms. In medical applications however, the sensitive nature of the data limits the collection and excha...
AJR. American journal of roentgenology
Aug 18, 2021
Sarcopenia is associated with adverse clinical outcomes. CT-based skeletal muscle measurements for sarcopenia assessment are most commonly performed at the L3 vertebral level. The purpose of this article is to compare the utility of fully automated...
INTRODUCTION: There is still a lack of availability of high-quality multiparametric magnetic resonance imaging (mpMRI) interpreted by experienced uro-radiologists to rule out clinically significant PC (csPC). Consequently, we developed a new imaging ...
Lung cancer is one of the most malignant tumors. If it can be detected early and treated actively, it can effectively improve a patient's survival rate. Therefore, early diagnosis of lung cancer is very important. Early-stage lung cancer usually appe...
OBJECTIVES: To compare the dose reduction potential (DRP) of a vendor-agnostic deep learning model (DLM, ClariCT.AI) with that of a vendor-specific deep learning-based image reconstruction algorithm (DLR, TrueFidelity™).
AIM: To evaluate a deep-learning-based computer-aided detection (DL-CAD) software system for pulmonary nodule detection on computed tomography (CT) images and assess its added value in the clinical practice of a large teaching hospital.
PURPOSE: Dual-source computed tomography (DSCT) uses two source-detector pairs offset by about 90°. In addition to the well-known forward scatter, a special issue in DSCT is cross-scattered radiation from X-ray tube A detected in the detector of syst...
BACKGROUND: Accurate measurement of hemorrhage volume is critical for both the prediction of prognosis and the selection of appropriate clinical treatment after spontaneous intracerebral hemorrhage (ICH). This study aimed to evaluate the performance ...
BACKGROUND: To assess the potential of radiomic features to quantify components of blood in intraaortic vessels to non-invasively predict moderate-to-severe anemia in non-contrast enhanced CT scans.
COVID-19 is a serious ongoing worldwide pandemic. Using X-ray chest radiography images for automatically diagnosing COVID-19 is an effective and convenient means of providing diagnostic assistance to clinicians in practice. This paper proposes a bagg...
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