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Improved detection of cholesterol gallstones using quasi-material decomposition images generated from single-energy computed tomography images via deep learning.

Radiological physics and technology
In this study, we developed a method for generating quasi-material decomposition (quasi-MD) images from single-energy computed tomography (SECT) images using a deep convolutional neural network (DCNN). Our aim was to improve the detection of choleste...

Predicting the impact of CPAP on brain health: A study using the sleep EEG-derived brain age index.

Annals of clinical and translational neurology
OBJECTIVE: This longitudinal study investigated potential positive impact of CPAP treatment on brain health in individuals with obstructive sleep Apnea (OSA). To allow this, we aimed to employ sleep electroencephalogram (EEG)-derived brain age index ...

Prescription eyeglasses as a forensic physical evidence: Prediction of age based on refractive error measures using machine learning algorithm.

Journal of forensic sciences
Refractive errors (RE) are commonly reported visual impairment problems worldwide. Previous clinical studies demonstrated age-related changes in human eyes. We hypothesized that the binocular RE metrics including sphere and cylinder power, axis orien...

Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester.

BMC pregnancy and childbirth
BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CU...

Deep learning for automatic bowel-obstruction identification on abdominal CT.

European radiology
RATIONALE AND OBJECTIVES: Automated evaluation of abdominal computed tomography (CT) scans should help radiologists manage their massive workloads, thereby leading to earlier diagnoses and better patient outcomes. Our objective was to develop a machi...

Diagnostic capabilities of artificial intelligence as an additional reader in a breast cancer screening program.

European radiology
OBJECTIVES: We aimed to evaluate the early-detection capabilities of AI in a screening program over its duration, with a specific focus on the detection of interval cancers, the early detection of cancers with the assistance of AI from prior visits, ...

An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks.

Journal of imaging informatics in medicine
Automated recognition of heart shunts using saline contrast transthoracic echocardiography (SC-TTE) has the potential to transform clinical practice, enabling non-experts to assess heart shunt lesions. This study aims to develop a fully automated and...

Towards an EKG for SBO: A Neural Network for Detection and Characterization of Bowel Obstruction on CT.

Journal of imaging informatics in medicine
A neural network was developed to detect and characterize bowel obstruction, a common cause of acute abdominal pain. In this retrospective study, 202 CT scans of 165 patients with bowel obstruction from March to June 2022 were included and partitione...

Improved 3D DESS MR neurography of the lumbosacral plexus with deep learning and geometric image combination reconstruction.

Skeletal radiology
OBJECTIVE: To evaluate the impact of deep learning (DL) reconstruction in enhancing image quality and nerve conspicuity in LSP MRN using DESS sequences. Additionally, a geometric image combination (GIC) method to improve DESS signals' combination was...