AIMC Topic: Deep Learning

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Correlation of vascular and fluid-related parameters in neovascular age-related macular degeneration using deep learning.

Acta ophthalmologica
PURPOSE: To identify correlations between the vascular characteristics of macular neovascularization (MNV) obtained by optical coherence tomography angiography (OCTA) and distinct retinal fluid volumes in neovascular age-related macular degeneration ...

Deep-learning prediction of amyloid deposition from early-phase amyloid positron emission tomography imaging.

Annals of nuclear medicine
OBJECTIVE: While the use of biomarkers for the detection of early and preclinical Alzheimer's Disease has become essential, the need to wait for over an hour after injection to obtain sufficient image quality can be challenging for patients with susp...

Development and Validation of a Deep Learning Model for Brain Tumor Diagnosis and Classification Using Magnetic Resonance Imaging.

JAMA network open
IMPORTANCE: Deep learning may be able to use patient magnetic resonance imaging (MRI) data to aid in brain tumor classification and diagnosis.

Deep Learning-Based Photoacoustic Imaging of Vascular Network Through Thick Porous Media.

IEEE transactions on medical imaging
Photoacoustic imaging is a promising approach used to realize in vivo transcranial cerebral vascular imaging. However, the strong attenuation and distortion of the photoacoustic wave caused by the thick porous skull greatly affect the imaging quality...

DeepGrading: Deep Learning Grading of Corneal Nerve Tortuosity.

IEEE transactions on medical imaging
Accurate estimation and quantification of the corneal nerve fiber tortuosity in corneal confocal microscopy (CCM) is of great importance for disease understanding and clinical decision-making. However, the grading of corneal nerve tortuosity remains ...

3D Segmentation Guided Style-Based Generative Adversarial Networks for PET Synthesis.

IEEE transactions on medical imaging
Potential radioactive hazards in full-dose positron emission tomography (PET) imaging remain a concern, whereas the quality of low-dose images is never desirable for clinical use. So it is of great interest to translate low-dose PET images into full-...

Motion Estimation by Deep Learning in 2D Echocardiography: Synthetic Dataset and Validation.

IEEE transactions on medical imaging
Motion estimation in echocardiography plays an important role in the characterization of cardiac function, allowing the computation of myocardial deformation indices. However, there exist limitations in clinical practice, particularly with regard to ...

Packaging Design Based on Deep Learning and Image Enhancement.

Computational intelligence and neuroscience
Packaging design is an important part of product design. How to improve the efficiency of packaging design is a problem that must be considered in product design. Existing packaging design methods require a lot of human and material resources. In vie...

A Comprehensive Survey of Abstractive Text Summarization Based on Deep Learning.

Computational intelligence and neuroscience
With the rapid development of the Internet, the massive amount of web textual data has grown exponentially, which has brought considerable challenges to downstream tasks, such as document management, text classification, and information retrieval. Au...