Improving retinal layer segmentation in rodent OCT images: A Semi-Supervised Learning Approach Using Graph-Cut Generated Pseudo Labels

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Original language	English
Title of host publication	Investigative Ophthalmology & Visual Science
Publication status	Published - 1 Jun 2024
Event	ARVO Annual Meeting 2024 - Seattle, United States Duration: 5 May 2024 → 9 May 2024

Cite this

@inproceedings{e4f6ff10deb346aa96703c17717a9f6b,

title = "Improving retinal layer segmentation in rodent OCT images: A Semi-Supervised Learning Approach Using Graph-Cut Generated Pseudo Labels",

author = "Zhengji Liu and Yingkun Cui and To, {Chi Ho} and Do, {Chi Wai} and Chun, {Ka Man}",

year = "2024",

month = jun,

day = "1",

language = "English",

booktitle = "Investigative Ophthalmology & Visual Science",

note = "ARVO Annual Meeting 2024 ; Conference date: 05-05-2024 Through 09-05-2024",

}

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Improving retinal layer segmentation in rodent OCT images: A Semi-Supervised Learning Approach Using Graph-Cut Generated Pseudo Labels

AU - Liu, Zhengji

AU - Cui, Yingkun

AU - To, Chi Ho

AU - Do, Chi Wai

AU - Chun, Ka Man

PY - 2024/6/1

Y1 - 2024/6/1

M3 - Conference article published in proceeding or book

BT - Investigative Ophthalmology & Visual Science

T2 - ARVO Annual Meeting 2024

Y2 - 5 May 2024 through 9 May 2024

ER -