AIMC Topic: Orbit
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Fully Automated Segmentation of Globes for Volume Quantification in CT Images of Orbits using Deep Learning.
AJNR. American journal of neuroradiology
May 21, 2020
BACKGROUND AND PURPOSE: Fast and accurate quantification of globe volumes in the event of an ocular trauma can provide clinicians with valuable diagnostic information. In this work, an automated workflow using a deep learning-based convolutional neur...
Deep learning segmentation of orbital fat to calibrate conventional MRI for longitudinal studies.
NeuroImage
Dec 9, 2019
In conventional non-quantitative magnetic resonance imaging, image contrast is consistent within images, but absolute intensity can vary arbitrarily between scans. For quantitative analysis of intensity data, images are typically normalized to a cons...
Orbit image analysis machine learning software can be used for the histological quantification of acute ischemic stroke blood clots.
PloS one
Dec 5, 2019
Our aim was to assess the utility of a novel machine learning software (Orbit Image Analysis) in the histological quantification of acute ischemic stroke (AIS) clots. We analyzed 50 AIS blood clots retrieved using mechanical thrombectomy procedures. ...
Ultrasound-guided posterior extraconal block in the dog: anatomical study in cadavers.
Veterinary anaesthesia and analgesia
Oct 11, 2018
OBJECTIVE: To describe a novel ultrasound-guided posterior extraconal block in the dog.
Deep Learning-Based CT Radiomics for Feature Representation and Analysis of Aging Characteristics of Asian Bony Orbit.
The Journal of craniofacial surgery
May 13, 2025
OBJECTIVE: This paper puts forward a new method for automatic segmentation of bony orbit as well as automatic extraction and classification of aging features of segmented orbit contour based on depth learning, with which the aging mode of bony orbit ...
Deep-Learning Based Automated Segmentation and Quantitative Volumetric Analysis of Orbital Muscle and Fat for Diagnosis of Thyroid Eye Disease.
Investigative ophthalmology & visual science
May 1, 2024
PURPOSE: Thyroid eye disease (TED) is characterized by proliferation of orbital tissues and complicated by compressive optic neuropathy (CON). This study aims to utilize a deep-learning (DL)-based automated segmentation model to segment orbital muscl...
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