Deep learning models are prone to failure when inferring upon out-of-distribution (OOD) data, i.e. data whose features fundamentally differ from those in the training set. Existing OOD measures often lack sensitivity to the subtle image variations en...
Kidney stone disease is a common syndrome and a recurring one, where it bears a 50% chance of being manifested again within ten years and may lead to serious complications like ureteral obstruction and unbearable pain. If timely intervention is consi...
BACKGROUND: Aortic dissection (AD) is a life-threatening condition. We developed an artificial intelligence (AI) algorithm capable of robust, accurate, and automated AD detection and sub-classification.
Primary pulmonary lung cancer is rare in dogs, and clinicians increasingly rely on advanced imaging for diagnosis and treatment planning. However, manual lesion segmentation can be time-consuming and subject to operator variability. This retrospectiv...
Aging clinical and experimental research
Oct 21, 2025
BACKGROUND: In order to identify patients with sarcopenia, the use of routine imaging could provide valuable support. One of the most common radiological examinations, especially in geriatric inpatient care, is CT thoracic imaging. Therefore, it woul...
European journal of cancer (Oxford, England : 1990)
Oct 20, 2025
STUDY AIM: Early detection of distant metastases is crucial, but current imaging detects them only when radiographically visible. This study reported subvisual chest CT signals could serve as early biomarkers for impending lung metastasis before radi...
Achieving high resolution while minimizing contrast agent dosage remains a key goal, yet a major challenge in contrast-enhanced computed tomography (CT) imaging. Herein, we propose an artificial intelligence-assisted low-dose high atomic number contr...
BACKGROUND: Accurate preoperative T and TNM staging of clear cell renal cell carcinoma (ccRCC) is crucial for diagnosis and treatment, but these assessments often depend on subjective radiologist judgment, leading to interobserver variability. This s...
Visceral pleural invasion (VPI) is a critical prognostic factor in early-stage non-small-cell lung cancer (NSCLC), significantly affecting patient outcomes. Conventional computed tomography (CT) often fails to diagnose VPI accurately. This retrospect...
BACKGROUND: Accurate prediction of prognosis and risk stratification in patients with laryngeal cancer can inform appropriate treatment decision-making. This study aims to develop a multi-channel deep learning radiomics model based on contrast-enhanc...
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