Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Qiangguo Jin"'
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 5, Pp 7265-7278 (2024)
Abstract Few-shot Semantic Segmentation (FSS) was proposed to segment unseen classes in a query image, referring to only a few annotated examples named support images. One of the characteristics of FSS is spatial inconsistency between query and suppo
Externí odkaz:
https://doaj.org/article/66b5252323d5415f89b661f712f00f9d
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 8 (2020)
Automatic extraction of liver and tumor from CT volumes is a challenging task due to their heterogeneous and diffusive shapes. Recently, 2D deep convolutional neural networks have become popular in medical image segmentation tasks because of the util
Externí odkaz:
https://doaj.org/article/4d387d15936740dbbe066027e63f9c0f
Publikováno v:
IEEE/ACM transactions on computational biology and bioinformatics.
Since abnormal expression of long non-coding RNAs (lncRNAs) is associated with various human diseases, identifying disease-related lncRNAs helps reveal the pathogenesis of diseases. Existing methods for lncRNA-disease association prediction mainly fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c91da4070eaffb4e4d1459186a05598d
https://pubmed.ncbi.nlm.nih.gov/36173783
https://pubmed.ncbi.nlm.nih.gov/36173783
Autor:
Ping Xuan, Hanwen Bi, Hui Cui, Qiangguo Jin, Tiangang Zhang, Huawei Tu, Peng Cheng, Changyang Li, Zhiyu Ning, Menghan guo, Henry B L Duh
Publikováno v:
Physics in medicine and biology. 67(22)
Objective. Effective learning and modelling of spatial and semantic relations between image regions in various ranges are critical yet challenging in image segmentation tasks. Approach. We propose a novel deep graph reasoning model to learn from mult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db3d1016c3b1dfc0f58a35834ae27505
https://pubmed.ncbi.nlm.nih.gov/36401576
https://pubmed.ncbi.nlm.nih.gov/36401576
Autor:
Ping Xuan, Bin Jiang, Hui Cui, Qiangguo Jin, Peng Cheng, Toshiya Nakaguchi, Tiangang Zhang, Changyang Li, Zhiyu Ning, Menghan Guo, Linlin Wang
Publikováno v:
Computer methods and programs in biomedicine. 226
Accurate lung tumor segmentation from computed tomography (CT) is complex due to variations in tumor sizes, shapes, patterns and growing locations. Learning semantic and spatial relations between different feature channels, image regions and position
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c31568df148a35c03b9750dd940b9a0
https://pubmed.ncbi.nlm.nih.gov/36206688
https://pubmed.ncbi.nlm.nih.gov/36206688
Publikováno v:
Neurocomputing. 385:300-309
Osteoporosis makes bones weak and brittle, increasing the risk of fracture. In this paper, we designed a hybrid model to diagnose osteoporosis based on bone radiograph images. Two types of features were used to distinguish between the “healthy” a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13f312dbecf5c80eb8a44b453a9bac51
https://doi.org/10.1016/j.neucom.2019.12.083
https://doi.org/10.1016/j.neucom.2019.12.083
Autor:
Qiangguo Jin, Hui Cui, Changming Sun, Jiangbin Zheng, Leyi Wei, Zhenyu Fang, Zhaopeng Meng, Ran Su
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031164330
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::125d6fe5eab562a2242858156bd1dcc3
https://doi.org/10.1007/978-3-031-16434-7_1
https://doi.org/10.1007/978-3-031-16434-7_1
Autor:
Tiangang Zhang, Kai Wang, Hui Cui, Qiangguo Jin, Peng Cheng, Toshiya Nakaguchi, Changyang Li, Zhiyu Ning, Linlin Wang, Ping Xuan
Publikováno v:
Physics in Medicine & Biology. 68:025007
Objective. Accurate and automated segmentation of lung tumors from computed tomography (CT) images is critical yet challenging. Lung tumors are of various sizes and locations and have indistinct boundaries adjacent to other normal tissues. Approach.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aba70ce341082122718a8a077bd8723f
https://doi.org/10.1088/1361-6560/acabff
https://doi.org/10.1088/1361-6560/acabff
Autor:
Ping Xuan, Xixi Wu, Hui Cui, Qiangguo Jin, Linlin Wang, Tiangang Zhang, Toshiya Nakaguchi, Henry B.L. Duh
Publikováno v:
Applied Soft Computing. 133:109905
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::851b58955621ec0ce90583f4e579b503
https://doi.org/10.1016/j.asoc.2022.109905
https://doi.org/10.1016/j.asoc.2022.109905
Publikováno v:
Knowledge-Based Systems. 178:149-162
Automatic segmentation of retinal vessels in fundus images plays an important role in the diagnosis of some diseases such as diabetes and hypertension. In this paper, we propose Deformable U-Net (DUNet), which exploits the retinal vessels’ local fe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ffdbcf8069ba03f053a6a5d11dc23d1
https://doi.org/10.1016/j.knosys.2019.04.025
https://doi.org/10.1016/j.knosys.2019.04.025