PELE scores: pelvic X-ray landmark detection with pelvis extraction and enhancement

doi:10.1007/s11548-024-03089-z

	PELE scores: pelvic X-ray landmark detection with pelvis extraction and enhancement
	Huang, Zhen 1,3; Li, Han 2,3; Shao, Shitong 4; Zhu, Heqin 2,3; Hu, Huijie 1,3; Cheng, Zhiwei 5; Wang, Jianji 6; Kevin Zhou, S.2,3,7
	2024-03-15
发表期刊	INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
ISSN	1861-6410
页码	12
摘要	PurposePelvic X-ray (PXR) is widely utilized in clinical decision-making associated with the pelvis, the lower part of the trunk that supports and balances the trunk. In particular, PXR-based landmark detection facilitates downstream analysis and computer-assisted diagnosis and treatment of pelvic diseases. Although PXR has the advantages of low radiation and reduced cost compared to computed tomography (CT), it characterizes the 2D pelvis-tissue superposition of 3D structures, which may affect the accuracy of landmark detection in some cases. However, the superposition nature of PXR is implicitly handled by existing deep learning-based landmark detection methods, which mainly design the deep network structures for better detection performances. Explicit handling of the superposition nature of PXR is rarely done.MethodsIn this paper, we explicitly focus on the superposition of X-ray images. Specifically, we propose a pelvis extraction (PELE) module that consists of a decomposition network, a domain adaptation network, and an enhancement module, which utilizes 3D prior anatomical knowledge in CT to guide and well isolate the pelvis from PXR, thereby eliminating the influence of soft tissue for landmark detection. The extracted pelvis image, after enhancement, is then used for landmark detection.ResultsWe conduct an extensive evaluation based on two public and one private dataset, totaling 850 PXRs. The experimental results show that the proposed PELE module significantly improves the accuracy of PXRs landmark detection and achieves state-of-the-art performances in several benchmark metrics.ConclusionThe design of PELE module can improve the accuracy of different pelvic landmark detection baselines, which we believe is obviously conducive to the positioning and inspection of clinical landmarks and critical structures, thus better serving downstream tasks. Our project has been open-sourced at https://github.com/ECNUACRush/PELEscores.
关键词	Bone extraction CT structural knowledge Landmark detection Pelvis X-rays
DOI	10.1007/s11548-024-03089-z
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation of China[62271465] ; Open Fund Project of Guangdong Academy of Medical Sciences, China[YKY-KF202206]
WOS研究方向	Engineering ; Radiology, Nuclear Medicine & Medical Imaging ; Surgery
WOS类目	Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging ; Surgery
WOS记录号	WOS:001184045700001
出版者	SPRINGER HEIDELBERG
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/38827
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Kevin Zhou, S.
作者单位	1.Univ Sci & Technol China, Comp Sci Dept, Hefei 230026, Peoples R China 2.Univ Sci & Technol China, Sch Biomed Engn, Div Life Sci & Med, Hefei 230026, Anhui, Peoples R China 3.Suzhou Inst Adv Res, Ctr Med Imaging Robot Analyt Comp & Learning MIRAC, USTC, Suzhou 215123, Peoples R China 4.Southeast Univ, Nanjing 210018, Peoples R China 5.Z2Sky Technol Inc, Suzhou 215123, Peoples R China 6.Guizhou Med Univ, Affiliated Hosp, Guiyang 550000, Peoples R China 7.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Huang, Zhen,Li, Han,Shao, Shitong,et al. PELE scores: pelvic X-ray landmark detection with pelvis extraction and enhancement[J]. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY,2024:12.
APA	Huang, Zhen.,Li, Han.,Shao, Shitong.,Zhu, Heqin.,Hu, Huijie.,...&Kevin Zhou, S..(2024).PELE scores: pelvic X-ray landmark detection with pelvis extraction and enhancement.INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY,12.
MLA	Huang, Zhen,et al."PELE scores: pelvic X-ray landmark detection with pelvis extraction and enhancement".INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2024):12.