Symmetry-Based Deep Learning Applying on Correlation between Nasal Structure and Complaints of Empty Nose Syndrome Patients

Wan, Shu-Yen (PI)
Fu, Chia Hsiang (CoPI)
Lee, Ta-Jen (CoPI)

Project: National Science and Technology Council › National Science and Technology Council Academic Grants

Abstract

本研究計畫係開發空鼻症影像分析的深度學習演算法，以及建立鼻腔結構與空鼻症病患主訴之間的預測模型。藉由此研究結果的呈現，醫生與病人可藉以在資訊透明且資訊平衡的基礎上討論臨床作為，增加手術的可預測性，進而提升醫療品質與手術規畫以及術後評估的能力。

Project IDs

Project ID:PB11107-7647
External Project ID:MOST111-2221-E182-019

Status	Finished
Effective start/end date	01/08/22 → 31/07/23

Keywords

Empty nose syndrome
Paranasal sinus
Nasal cavity symmetry
Turbinates
Deep learning
Symmetry-based deep learning algorithm

Access Project

https://www.grb.gov.tw/search/planDetail?id=14506997