| 题名 | JOINED: Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection |
| 作者 | |
| 通讯作者 | Tang, Xiaoying |
| 发表日期 | 2022-12-04
|
| 会议名称 | Medical Imaging with Deep Learning (MIDL)
|
| 会议录名称 | |
| 页码 | 477-492
|
| 会议日期 | 6-8July，2022
|
| 会议地点 | Zurich, Switzerland
|
| 摘要 | Fundus photography has been routinely used to document the presence and severity of
various retinal degenerative diseases such as age-related macula degeneration, glaucoma,
and diabetic retinopathy, for which the fovea, optic disc (OD), and optic cup (OC) are
important anatomical landmarks. Identifification of those anatomical landmarks is of great
clinical importance. However, the presence of lesions, drusen, and other abnormalities
during retinal degeneration severely complicates automatic landmark detection and seg
mentation. Most existing works treat the identifification of each landmark as a single task
and typically do not make use of any clinical prior information. In this paper, we present
a novel method, named JOINED, for prior guided multi-task learning for joint OD/OC
segmentation and fovea detection. An auxiliary branch for distance prediction, in addi
tion to a segmentation branch and a detection branch, is constructed to effffectively utilize
the distance information from each image pixel to landmarks of interest. Our proposed
JOINED pipeline consists of a coarse stage and a fifine stage. At the coarse stage, we obtain
the OD/OC coarse segmentation and the heatmap localization of fovea through a joint seg
mentation and detection module. Afterwards, we crop the regions of interest for subsequent
fifine processing and use predictions obtained at the coarse stage as additional information
for better performance and faster convergence. Experimental results reveal that our pro
posed JOINED outperforms existing state-of-the-art approaches on the publicly-available
GAMMA, PALM, and REFUGE datasets of fundus images. Furthermore, JOINED ranked
the 5th on the OD/OC segmentation and fovea detection tasks in the GAMMA challenge
hosted by the MICCAI2021 workshop OMIA8. |
| 关键词 | |
| 学校署名 | 第一
; 通讯
|
| 语种 | 英语
|
| 来源库 | 人工提交
|
| 全文链接 | https://openreview.net/pdf?id=HU6-t9oKvRW |
| 出版状态 | 正式出版
|
| 成果类型 | 会议论文 |
| 条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/527496 |
| 专题 | 南方科技大学 工学院_电子与电气工程系 |
| 作者单位 | 1.Southern University of Science and Technology,Shenzhen, China 2.The University of Hong Kong,Hong Kong, China;Southern University of Science and Technology,Shenzhen, China |
| 第一作者单位 | 南方科技大学 |
| 通讯作者单位 | 南方科技大学 |
| 第一作者的第一单位 | 南方科技大学 |
| 推荐引用方式 GB/T 7714 |
He, Huaqing,Lin, Li,Cai, Zhiyuan,et al. JOINED: Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection[C],2022:477-492.
|
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | 操作 | |
| JOINED Prior Guided （1609KB） | -- | -- | 限制开放 | -- | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
修改评论