AIMC Topic: Pupil

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Deep learning of spontaneous arousal fluctuations detects early cholinergic defects across neurodevelopmental mouse models and patients.

Proceedings of the National Academy of Sciences of the United States of America Jul 22, 2019
Neurodevelopmental spectrum disorders like autism (ASD) are diagnosed, on average, beyond age 4 y, after multiple critical periods of brain development close and behavioral intervention becomes less effective. This raises the urgent need for quantita...
Cohort Studies Mice Male Deep Learning Acetylcholine Autistic Disorder Disease Models, Animal Protein Serine-Threonine Kinases Humans Female Animals Rett Syndrome Arousal Methyl-CpG-Binding Protein 2 Pupil
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DeepVOG: Open-source pupil segmentation and gaze estimation in neuroscience using deep learning.

Journal of neuroscience methods Jun 6, 2019
BACKGROUND: A prerequisite for many eye tracking and video-oculography (VOG) methods is an accurate localization of the pupil. Several existing techniques face challenges in images with artifacts and under naturalistic low-light conditions, e.g. with...
Fixation, Ocular Pupil Neurosciences Video Recording Adult Male Deep Learning Image Processing, Computer-Assisted Humans Female
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Pupil-Linked Arousal is Predictive of Team Performance in a Virtual Reality (VR) Sensory-Motor Task.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The performance of teams can be significantly affected by the physiological arousal of each team member. Pupil dynamics has been shown to index, among other things, arousal. In this paper, we describe a multi-person virtual reality (VR) based sensory...
Young Adult Humans Arousal Adult Psychomotor Performance Female Pupil Task Performance and Analysis Male Virtual Reality
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PhacoTrainer: Deep Learning for Cataract Surgical Videos to Track Surgical Tools.

Translational vision science & technology Mar 1, 2023
PURPOSE: The purpose of this study was to build a deep-learning model that automatically analyzes cataract surgical videos for the locations of surgical landmarks, and to derive skill-related motion metrics.
Humans Algorithms Cataract Pupil Deep Learning Cataract Extraction
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Neural network model assisted Fourier ptychography with Zernike aberration recovery and total variation constraint.

Journal of biomedical optics Mar 1, 2021
SIGNIFICANCE: Fourier ptychography (FP) is a computational imaging approach that achieves high-resolution reconstruction. Inspired by neural networks, many deep-learning-based methods are proposed to solve FP problems. However, the performance of FP ...
Artifacts Pupil Tomography, X-Ray Computed Neural Networks, Computer Image Processing, Computer-Assisted
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[Clinical and theoretical substantiation of geometrical, optical and functional features of the pupil of the artificial iris].

Vestnik oftalmologii Jan 1, 2019
UNLABELLED: Presence of an extensive iris defect requires implantation of artificial iris (AI) to close it. With biometric parameters of the AI being as close to an intact eye as possible, it becomes viable to achieve good clinical and functional res...
Aniridia Iris Pupil Lenses, Intraocular Humans Visual Acuity
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Analyzing the Time Course of Pupillometric Data.

Trends in hearing Jan 1, 2019
This article provides a tutorial for analyzing pupillometric data. Pupil dilation has become increasingly popular in psychological and psycholinguistic research as a measure to trace language processing. However, there is no general consensus about p...
Female Male Humans Natural Language Processing Pupil Psychometrics Regression Analysis
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