PURPOSE: To investigate whether the deep learning reconstruction (DLR) combined with contrast-enhancement-boost (CE-boost) technique can improve the diagnostic quality of CT pulmonary angiography (CTPA) at low radiation and contrast doses, compared w...
OBJECTIVES: To evaluate the variability of fully automated airway quantitative CT (QCT) measures caused by different kernels and the effect of kernel conversion.
International journal of computer assisted radiology and surgery
Nov 1, 2025
PURPOSE: Assessment of intraoperative surgical skill is necessary to train surgeons and certify them for practice. The generalizability of deep learning models for video-based assessment (VBA) of surgical skill has not yet been evaluated. In this wor...
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Nov 1, 2025
Artificial Intelligence (AI) is transforming neuro-oncology by enhancing diagnosis, treatment planning, and prognosis prediction. AI-driven approaches-such as CNNs and deep learning-have improved the detection and classification of brain tumors throu...
OBJECTIVES: To investigate whether a content-based image retrieval (CBIR) of similar chest CT images can help usual interstitial pneumonia (UIP) CT pattern classifications among readers with varying levels of experience.
OBJECTIVES: This study aimed to compare the diagnostic performance of CT-derived fractional flow reserve (CT-FFR) using model-based iterative reconstruction (MBIR) and high-resolution deep learning reconstruction (HR-DLR) images to detect functionall...
BACKGROUND: Most of the focus regarding total knee arthroplasty (TKA) implant positioning and alignment has been centered on the coronal plane. Posterior condylar offset (PCO) and tibial slope (TS) are sagittal parameters that are measured on radiogr...
OBJECTIVES: To perform a systematic review on the impact of deep learning (DL)-based triage for reducing diagnostic delays and improving patient outcomes in peer-reviewed and pre-print publications.
PURPOSE: Accurate assessment of cystoid macular oedema (CMO) in patients with retinitis pigmentosa (RP) on spectral-domain optical coherence tomography (SD-OCT) is crucial for tracking disease progression and may serve as a therapeutic endpoint. Manu...
OBJECTIVES: This study aims to develop a deep learning algorithm for differentiating aneurysmal subarachnoid hemorrhage (aSAH) from non-aneurysmal subarachnoid hemorrhage (naSAH) using non-contrast computed tomography (NCCT) scans.
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