AIMC Topic: Deep Learning

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Rapid high-fidelity mapping using single-shot overlapping-echo acquisition and deep learning reconstruction.

Magnetic resonance in medicine
PURPOSE: To develop and evaluate a single-shot quantitative MRI technique called GRE-MOLED (gradient-echo multiple overlapping-echo detachment) for rapid mapping.

Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat).

Medical image analysis
Diffusion MRI is a useful neuroimaging tool for non-invasive mapping of human brain microstructure and structural connections. The analysis of diffusion MRI data often requires brain segmentation, including volumetric segmentation and cerebral cortic...

Evaluation of generalization ability for deep learning-based auto-segmentation accuracy in limited field of view CBCT of male pelvic region.

Journal of applied clinical medical physics
PURPOSE: The aim of this study was to evaluate generalization ability of segmentation accuracy for limited FOV CBCT in the male pelvic region using a full-image CNN. Auto-segmentation accuracy was evaluated using various datasets with different inten...

Deep Learning for Differentiation of Breast Masses Detected by Screening Ultrasound Elastography.

Ultrasound in medicine & biology
Recently, deep learning using convolutional neural networks (CNNs) has yielded consistent results in image-pattern recognition. This study was aimed at investigating the effectiveness of deep learning using CNNs to differentiate benign and malignant ...

Image Noise Removal in Ultrasound Breast Images Based on Hybrid Deep Learning Technique.

Sensors (Basel, Switzerland)
Rapid improvements in ultrasound imaging technology have made it much more useful for screening and diagnosing breast problems. Local-speckle-noise destruction in ultrasound breast images may impair image quality and impact observation and diagnosis....

Rapid Identification of Infectious Pathogens at the Single-Cell Level via Combining Hyperspectral Microscopic Images and Deep Learning.

Cells
Identifying infectious pathogens quickly and accurately is significant for patients and doctors. Identifying single bacterial strains is significant in eliminating culture and speeding up diagnosis. We present an advanced optical method for the rapid...

The predictive value of deep learning-based cardiac ultrasound flow imaging for hypertrophic cardiomyopathy complicating arrhythmias.

European journal of medical research
OBJECTIVE: To investigate the predictive value of deep learning-based cardiac ultrasound flow imaging for hypertrophic cardiomyopathy (HCM) complicated by arrhythmias.

The classification of flash visual evoked potential based on deep learning.

BMC medical informatics and decision making
BACKGROUND: Visual electrophysiology is an objective visual function examination widely used in clinical work and medical identification that can objectively evaluate visual function and locate lesions according to waveform changes. However, in visua...

A deep learning model incorporating spatial and temporal information successfully detects visual field worsening using a consensus based approach.

Scientific reports
Glaucoma is a leading cause of irreversible blindness, and its worsening is most often monitored with visual field (VF) testing. Deep learning models (DLM) may help identify VF worsening consistently and reproducibly. In this study, we developed and ...

Video-based formative and summative assessment of surgical tasks using deep learning.

Scientific reports
To ensure satisfactory clinical outcomes, surgical skill assessment must be objective, time-efficient, and preferentially automated-none of which is currently achievable. Video-based assessment (VBA) is being deployed in intraoperative and simulation...