BACKGROUND: Haemorrhage transformation (HT) is a serious complication of intravenous thrombolysis (IVT) in acute ischaemic stroke (AIS). Accurate and timely prediction of the risk of HT before IVT may change the treatment decision and improve clinica...
Journal of neurointerventional surgery
Dec 19, 2023
BACKGROUND: Automated measurement of the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) can support clinical decision making. Based on a deep learning algorithm, we developed an automated ASPECTS scoring system (Heuron ASPECTS) and ...
Journal of computer assisted tomography
Dec 18, 2023
OBJECTIVE: The aim of the study is to assess the correlation between artificial intelligence (AI)-based low attenuation volume percentage (LAV%) with forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) and visual emphysem...
BACKGROUND: Semi-supervised learning has gained popularity in medical image segmentation due to its ability to reduce reliance on image annotation. A typical approach in semi-supervised learning is to select reliable predictions as pseudo-labels and ...
BACKGROUND: The accurate identification and evaluation of lymph nodes by CT images is of great significance for disease diagnosis, treatment, and prognosis.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dec 15, 2023
Accurate lymph node size estimation is critical for staging cancer patients, initial therapeutic management, and assessing response to therapy. Current standard practice for quantifying lymph node size is based on a variety of criteria that use uni-d...
Computer methods and programs in biomedicine
Dec 14, 2023
BACKGROUND AND OBJECTIVE: Renal cell carcinoma represents a significant global health challenge with a low survival rate. The aim of this research was to devise a comprehensive deep-learning model capable of predicting survival probabilities in patie...
COVID-19 has potential consequences on the pulmonary and cardiovascular health of millions of infected people worldwide. Chest computed tomographic (CT) imaging has remained the first line of diagnosis for individuals infected with SARS-CoV-2. Howeve...
OBJECTIVES: To evaluate the relationship of changes in the deep learning-based CT quantification of interstitial lung disease (ILD) with changes in forced vital capacity (FVC) and visual assessments of ILD progression, and to investigate their progno...
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