AIMC Topic: Deep Learning

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Application of Deep Learning for Automated Detection of Polypoidal Choroidal Vasculopathy in Spectral Domain Optical Coherence Tomography.

Translational vision science & technology
OBJECTIVE: To develop an automated polypoidal choroidal vasculopathy (PCV) screening model to distinguish PCV from wet age-related macular degeneration (wet AMD).

Deep Learning Segmentation, Visualization, and Automated 3D Assessment of Ciliary Body in 3D Ultrasound Biomicroscopy Images.

Translational vision science & technology
PURPOSE: This study aimed to develop a fully automated deep learning ciliary body segmentation and assessment approach in three-dimensional ultrasound biomicroscopy (3D-UBM) images.

Rapid lipid-laden plaque identification in intravascular optical coherence tomography imaging based on time-series deep learning.

Journal of biomedical optics
SIGNIFICANCE: Coronary heart disease has the highest rate of death and morbidity in the Western world. Atherosclerosis is an asymptomatic condition that is considered the primary cause of cardiovascular diseases. The accumulation of low-density lipop...

Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging.

Journal of biomedical optics
SIGNIFICANCE: Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image representation. Nonlinear optical fluence correction in OA imagin...

Artificial Intelligence and Deep Learning for Brachytherapy.

Seminars in radiation oncology
In recent years, Artificial intelligence (AI), specifically deep-learning (DL) based methods, have been employed extensively to solve various problems in brachytherapy. This paper presents a comprehensive literature review on recent developments and ...

Potential of Deep Learning in Quantitative Magnetic Resonance Imaging for Personalized Radiotherapy.

Seminars in radiation oncology
Quantitative magnetic resonance imaging (qMRI) has been shown to provide many potential advantages for personalized adaptive radiotherapy (RT). Deep learning models have proven to increase efficiency, robustness and speed for different qMRI tasks. Th...

Uncertainty Assessment for Deep Learning Radiotherapy Applications.

Seminars in radiation oncology
In the last 5 years, deep learning applications for radiotherapy have undergone great development. An advantage of radiotherapy over radiological applications is that data in radiotherapy are well structured, standardized, and annotated. Furthermore,...

Spatially variant deblur and image enhancement in a single multimode fiber imaged by deep learning.

Optics letters
A single multimode fiber has been applied in minimally invasive endoscopy with wavefront shaping for biological research such as brain imaging. Most of the fibers, such as step-index and graded-index multimode fibers, give rise to spatially variant b...

Feasibility of Deep Learning-Based Analysis of Auscultation for Screening Significant Stenosis of Native Arteriovenous Fistula for Hemodialysis Requiring Angioplasty.

Korean journal of radiology
OBJECTIVE: To investigate the feasibility of using a deep learning-based analysis of auscultation data to predict significant stenosis of arteriovenous fistulas (AVF) in patients undergoing hemodialysis requiring percutaneous transluminal angioplasty...