干旱区生态环境知识资源中心(Arid): RETRACTED: MeQryEP: A Texture Based Descriptor for Biomedical Image Retrieval (Retracted Article)

Arid

DOI	10.1155/2022/9505229
	RETRACTED: MeQryEP: A Texture Based Descriptor for Biomedical Image Retrieval (Retracted Article)
	Deep, G.; Kaur, J.; Singh, Simar Preet; Nayak, Soumya Ranjan; Kumar, Manoj; Kautish, Sandeep
通讯作者	Kautish, S
来源期刊	JOURNAL OF HEALTHCARE ENGINEERING
ISSN	2040-2295
EISSN	2040-2309
出版年	2022
卷号	2022
英文摘要	Image texture analysis is a dynamic area of research in computer vision and image processing, with applications ranging from medical image analysis to image segmentation to content-based image retrieval and beyond. Quinary encoding on mesh patterns (MeQryEP) is a new approach to extracting texture features for indexing and retrieval of biomedical images, which is implemented in this work. An extension of the previous study, this research investigates the use of local quinary patterns (LQP) on mesh patterns in three different orientations. To encode the gray scale relationship between the central pixel and its surrounding neighbors in a two-dimensional (2D) local region of an image, binary and nonbinary coding, such as local binary patterns (LBP), local ternary patterns (LTP), and LQP, are used, while the proposed strategy uses three selected directions of mesh patterns to encode the gray scale relationship between the surrounding neighbors for a given center pixel in a 2D image. An innovative aspect of the proposed method is that it makes use of mesh image structure quinary pattern features to encode additional spatial structure information, resulting in better retrieval. On three different kinds of benchmark biomedical data sets, analyses have been completed to assess the viability of MeQryEP. LIDC-IDRI-CT and VIA/I-ELCAP-CT are the lung image databases based on computed tomography (CT), while OASIS-MRI is a brain database based on magnetic resonance imaging (MRI). This method outperforms state-of-the-art texture extraction methods, such as LBP, LQEP, LTP, LMeP, LMeTerP, DLTerQEP, LQEQryP, and so on in terms of average retrieval precision (ARP) and average retrieval rate (ARR).
类型	Article ; Retracted Publication
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000814125400028
WOS关键词	LOCAL BINARY PATTERNS ; EXTREMA PATTERN ; CLASSIFICATION ; MRI ; FEATURES ; SYSTEM
WOS类目	Health Care Sciences & Services
WOS研究方向	Health Care Sciences & Services
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/393470
推荐引用方式 GB/T 7714	Deep, G.,Kaur, J.,Singh, Simar Preet,et al. RETRACTED: MeQryEP: A Texture Based Descriptor for Biomedical Image Retrieval (Retracted Article)[J],2022,2022.
APA	Deep, G.,Kaur, J.,Singh, Simar Preet,Nayak, Soumya Ranjan,Kumar, Manoj,&Kautish, Sandeep.(2022).RETRACTED: MeQryEP: A Texture Based Descriptor for Biomedical Image Retrieval (Retracted Article).JOURNAL OF HEALTHCARE ENGINEERING,2022.
MLA	Deep, G.,et al."RETRACTED: MeQryEP: A Texture Based Descriptor for Biomedical Image Retrieval (Retracted Article)".JOURNAL OF HEALTHCARE ENGINEERING 2022(2022).