AIMC Topic: Deep Learning

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A contextual detector of surgical tools in laparoscopic videos using deep learning.

Surgical endoscopy
BACKGROUND: The complexity of laparoscopy requires special training and assessment. Analyzing the streaming videos during the surgery can potentially improve surgical education. The tedium and cost of such an analysis can be dramatically reduced usin...

Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study.

Sleep & breathing = Schlaf & Atmung
PURPOSE: In 2-dimensional lateral cephalometric radiographs, patients with severe obstructive sleep apnea (OSA) exhibit a more crowded oropharynx in comparison with non-OSA. We tested the hypothesis that machine learning, an application of artificial...

Deep learning-based differentiation of invasive adenocarcinomas from preinvasive or minimally invasive lesions among pulmonary subsolid nodules.

European radiology
OBJECTIVES: To evaluate a deep learning-based model using model-generated segmentation masks to differentiate invasive pulmonary adenocarcinoma (IPA) from preinvasive lesions or minimally invasive adenocarcinoma (MIA) on CT, making comparisons with r...

Deep Learning With 3D Convolutional Neural Network for Noninvasive Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Microvascular invasion (MVI) is a critical prognostic factor of hepatocellular carcinoma (HCC). However, it could only be obtained by postoperative histological examination.

Deep learning-based T1-enhanced selection of linear attenuation coefficients (DL-TESLA) for PET/MR attenuation correction in dementia neuroimaging.

Magnetic resonance in medicine
PURPOSE: The accuracy of existing PET/MR attenuation correction (AC) has been limited by a lack of correlation between MR signal and tissue electron density. Based on our finding that longitudinal relaxation rate, or R , is associated with CT Hounsfi...

Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality.

Nature biomedical engineering
Machine learning promises to assist physicians with predictions of mortality and of other future clinical events by learning complex patterns from historical data, such as longitudinal electronic health records. Here we show that a convolutional neur...

A deep-learning semantic segmentation approach to fully automated MRI-based left-ventricular deformation analysis in cardiotoxicity.

Magnetic resonance imaging
Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to breast cancer chemotherapy. This study investigated an automated LV ch...

Tactile Avatar: Tactile Sensing System Mimicking Human Tactile Cognition.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
As a surrogate for human tactile cognition, an artificial tactile perception and cognition system are proposed to produce smooth/soft and rough tactile sensations by its user's tactile feeling; and named this system as "tactile avatar". A piezoelectr...