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DCNN Developed for Detection and Assessing the Perfusion of PTG
Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Summary
Since the anatomical location and appearance of the parathyroid gland (PTG) vary, detection of the PTG and preserving the blood supply are among the difficulties encountered during a thyroidectomy procedure. We are planning to train a deep convolutional neural network based on a larger sample of endoscopic images to develop a model to assist surgeons in detection of PTG during endoscopic thyroidectomy. Furthermore, we would like to train a DCNN to predict blood perfusion based on endoscopic images comparing to indocyanine green fluorescence angiography as reference standard, and assess the performance of DCNN in predicting postoperative hypoparathyroidism.
Official title: Development and Improvement of a Deep Convolutional Neural Network for Detection and Assessing the Perfusion of Parathyroid Gland During Endoscopic Thyroidectomy
Key Details
Gender
All
Age Range
18 Years - 70 Years
Study Type
OBSERVATIONAL
Enrollment
300
Start Date
2023-06-13
Completion Date
2026-10
Last Updated
2025-12-03
Healthy Volunteers
No
Conditions
Interventions
a deep convolutional neural network
a deep convolutional neural network developed for detection and assessing the perfusion of parathyroid gland during endoscopic thyroidectomy
Locations (1)
Sun Yat-sen Memorial Hospital
Guangzhou, Guangdong, China