OBJECTIVE: Low monoenergetic images obtained using noise-reduction techniques may reduce CT contrast media requirements. We aimed to investigate the effectiveness of low-contrast-dose CT using dual-energy CT and deep learning-based denoising (DLD) te...
OBJECTIVES: Lymph node (LN) metastasis is a common cause of recurrence in oral cancer; however, the accuracy of distinguishing positive and negative LNs is not ideal. Here, we aimed to develop a deep learning model that can identify, locate, and dist...
BACKGROUND: The applicability and accuracy of artificial intelligence (AI)-assisted bone age assessment and adult height prediction methods in girls with early puberty are unknown.
Journal of applied clinical medical physics
Dec 28, 2022
PURPOSE: The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method was retrospectively studied with orthogonal kV X-ray images and clinical tracking records acquired during lung cancer treatment.
OBJECTIVE: In this study, we investigate the feasibility of a deep Convolutional Neural Network (dCNN), trained with mammographic images, to detect and classify microcalcifications (MC) in breast-CT (BCT) images.
Robot-assisted partial nephrectomy (RAPN) has traditionally been performed as an inpatient procedure; however, recent studies have suggested the feasibility of same-day discharge (SDD) after RAPN. We aimed to evaluate the safety and cost-effectivene...
PURPOSE: This study is to compare the precision and safety of the orthopaedic robot with conventional fluoroscopy for assisted percutaneous sacroiliac joint screw implantation.
The aim of this study is to report our experience in minimally invasive management of rectovesical fistulae (RVFs). Between 2004 and 2021, 24 patients who underwent minimally invasive RVF repair by a single surgeon at 3 international institutions w...
Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
Dec 26, 2022
BACKGROUND: Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine nonc...
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Dec 26, 2022
PURPOSE: To perform patellofemoral joint (PFJ) geometric measurements on knee magnetic resonance imaging scans and determine their relations with chondral lesions in a multicenter cohort using deep learning.
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