RATIONALE AND OBJECTIVES: We aim to develop a CT-based deep learning (DL) system for fully automatic segmentation of regional muscle volume and measurement of the spatial intermuscular fat distribution of the gluteus maximus muscle.
Journal of computer assisted tomography
Jul 7, 2023
OBJECTIVES: This study aimed to develop a computed tomography (CT)-based deep learning model for assessing the severity of patients with connective tissue disease (CTD)-associated interstitial lung disease (ILD).
International journal of computer assisted radiology and surgery
Jul 7, 2023
PURPOSE: Medical imaging can be used to estimate a patient's biological age, which may provide complementary information to clinicians compared to chronological age. In this study, we aimed to develop a method to estimate a patient's age based on the...
Recent advances in artificial intelligence (AI) for cardiac computed tomography (CT) have shown great potential in enhancing diagnosis and prognosis prediction in patients with cardiovascular disease. Deep learning, a type of machine learning, has re...
PURPOSE: To evaluate the image quality and visibility of pancreatic ductal adenocarcinoma (PDAC) in 80-kVp pancreatic CT protocol and compare them between hybrid-iterative reconstruction (IR) and deep-learning image reconstruction (DLIR) algorithms.
OBJECTIVES: To develop a deep learning (DL) method that can determine the Liver Imaging Reporting and Data System (LI-RADS) grading of high-risk liver lesions and distinguish hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT.
International journal of surgery (London, England)
Jul 1, 2023
BACKGROUND: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of locally advanced gastric cancer (LAGC). The aim of this study was to identify radio-clinical signatur...
Journal of computer assisted tomography
Jun 30, 2023
OBJECTIVE: Noise quantification is fundamental to computed tomography (CT) image quality assessment and protocol optimization. This study proposes a deep learning-based framework, Single-scan Image Local Variance EstimatoR (SILVER), for estimating th...
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Jun 30, 2023
We investigated the effect of deep learning reconstruction (DLR) plus single-energy metal artifact reduction (SEMAR) on neck CT in patients with dental metals, comparing it with DLR and with hybrid iterative reconstruction (Hybrid IR)-SEMAR. In thi...
OBJECTIVES: This study aims to develop a deep learning algorithm, Pneumonia-Plus, based on computed tomography (CT) images for accurate classification of bacterial, fungal, and viral pneumonia.
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