AIMC Topic: Deep Learning

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Diagnostic and Gradation Model of Osteoporosis Based on Improved Deep U-Net Network.

Journal of medical systems
The measurement of bone mineral density for osteoporosis has always been the focus of researchers because it plays an important role in bone disease diagnosis. However, because of X-ray image noise and the large difference between the bone shapes of ...

Deep learning: definition and perspectives for thoracic imaging.

European radiology
Relevance and penetration of machine learning in clinical practice is a recent phenomenon with multiple applications being currently under development. Deep learning-and especially convolutional neural networks (CNNs)-is a subset of machine learning,...

The clinical feasibility of deep learning-based classification of amyloid PET images in visually equivocal cases.

European journal of nuclear medicine and molecular imaging
PURPOSE: Although most deep learning (DL) studies have reported excellent classification accuracy, these studies usually target typical Alzheimer's disease (AD) and normal cognition (NC) for which conventional visual assessment performs well. A clini...

Deep Learning for Automated Measurement of Hemorrhage and Perihematomal Edema in Supratentorial Intracerebral Hemorrhage.

Stroke
Background and Purpose- Volumes of hemorrhage and perihematomal edema (PHE) are well-established biomarkers of primary and secondary injury, respectively, in spontaneous intracerebral hemorrhage. An automated imaging pipeline capable of accurately an...

A Deep Learning Framework for Design and Analysis of Surgical Bioprosthetic Heart Valves.

Scientific reports
Bioprosthetic heart valves (BHVs) are commonly used as heart valve replacements but they are prone to fatigue failure; estimating their remaining life directly from medical images is difficult. Analyzing the valve performance can provide better guida...

Comparing deep learning-based auto-segmentation of organs at risk and clinical target volumes to expert inter-observer variability in radiotherapy planning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND: Deep learning-based auto-segmented contours (DC) aim to alleviate labour intensive contouring of organs at risk (OAR) and clinical target volumes (CTV). Most previous DC validation studies have a limited number of expert observers for com...

Using 3D Convolutional Neural Networks for Tactile Object Recognition with Robotic Palpation.

Sensors (Basel, Switzerland)
In this paper, a novel method of active tactile perception based on 3D neural networks and a high-resolution tactile sensor installed on a robot gripper is presented. A haptic exploratory procedure based on robotic palpation is performed to get press...