ODDF-Net: Multi-object segmentation in 3D retinal OCTA using optical density and disease features

doi:10.1016/j.knosys.2024.112704

	ODDF-Net: Multi-object segmentation in 3D retinal OCTA using optical density and disease features
	Yang, Chaozhi 1; Fan, Jiayue 1; Bai, Yun 1; Li, Yachuan 1; Xiao, Qian 1; Li, Zongmin 1; Li, Hongyi 2; Li, Hua 3
	2024-12-20
发表期刊	KNOWLEDGE-BASED SYSTEMS
ISSN	0950-7051
卷号	306 页码:13
摘要	Automatic extraction of retinal structures, including Retinal Capillaries (RC), Retinal Arteries (RA), Retinal Veins (RV), and the Foveal Avascular Zone (FAZ), is crucial for the diagnosis and treatment of ocular diseases. This paper presents ODDF-Net, a segmentation network leveraging optical density and disease features, for the simultaneous 2D segmentation of RC, RA, RV, and FAZ in 3D Optical Coherence Tomography Angiography (OCTA). We introduce the concept of optical density to generate additional input images, enhancing the specificity for distinguishing arteries and veins. Our network employs a decoupled segmentation head to separate independent features of each object from shared features by focusing on object boundaries. Given the impact of ocular diseases on the morphology of retinal objects, we designed an auxiliary classification head and a cross-dimensional feature fusion module to model the relationship between various diseases and changes in retinal structures. Extensive experiments on two subsets of the OCTA-500 dataset demonstrate that ODDF-Net outperforms state-of-the-art methods, achieving mean intersection over union ratios of 88.17% and 82.80%. The source code is available at https://github.com/y8421036/ODDF-Net.
关键词	Multi-object segmentation Retina OCTA Optical density 3D to 2D
DOI	10.1016/j.knosys.2024.112704
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China[2019YFF0301800] ; National Natural Science Foundation of China[61379106] ; National Natural Science Foundation of China[61806199] ; General Research Projects of Beijing Educations Committee in China[KM201910005013] ; Shandong Provincial Natural Science Foundation[ZR2015FM011]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:001357509600001
出版者	ELSEVIER
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41191
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Zongmin
作者单位	1.China Univ Petr East China, Coll Comp Sci & Technol, Qingdao 266580, Peoples R China 2.Chinese Acad Med Sci, Beijing Hosp, Inst Geriatr Med, Beijing 100730, Peoples R China 3.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Yang, Chaozhi,Fan, Jiayue,Bai, Yun,et al. ODDF-Net: Multi-object segmentation in 3D retinal OCTA using optical density and disease features[J]. KNOWLEDGE-BASED SYSTEMS,2024,306:13.
APA	Yang, Chaozhi.,Fan, Jiayue.,Bai, Yun.,Li, Yachuan.,Xiao, Qian.,...&Li, Hua.(2024).ODDF-Net: Multi-object segmentation in 3D retinal OCTA using optical density and disease features.KNOWLEDGE-BASED SYSTEMS,306,13.
MLA	Yang, Chaozhi,et al."ODDF-Net: Multi-object segmentation in 3D retinal OCTA using optical density and disease features".KNOWLEDGE-BASED SYSTEMS 306(2024):13.