AI-based automated Meibomian gland segmentation, classification and reflection correction in infrared Meibography

no code implementations • 31 May 2022 • Ripon Kumar Saha, A. M. Mahmud Chowdhury, Kyung-Sun Na, Gyu Deok Hwang, Youngsub Eom, Jaeyoung Kim, Hae-Gon Jeon, Ho Sik Hwang, Euiheon Chung

Purpose: Develop a deep learning-based automated method to segment meibomian glands (MG) and eyelids, quantitatively analyze the MG area and MG ratio, estimate the meiboscore, and remove specular reflections from infrared images.

Generative Adversarial Network Segmentation

Holistic random encoding for imaging through multimode fibers

no code implementations • 30 Dec 2014 • Hwanchol Jang, Changhyeong Yoon, Euiheon Chung, Wonshik Choi, Heung-No Lee

In this paper, we aim to improve the signal to noise ratio (SNR) of the image reconstruction in imaging through MMF.

Image Reconstruction