Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Rusong Meng"'
Autor:
Wenmin Fei, Yang Han, Ang Li, Keke Li, Xiaoli Ning, Chengxu Li, Wenju Wang, Rusong Meng, Yong Cui, Lishao Guo
Publikováno v:
Chinese Medical Journal, Vol 135, Iss 12, Pp 1444-1450 (2022)
Abstract. Background:. The dermoscopic features of rosacea have already been reported. However, the current findings are incomplete, and little is known about phymatous rosacea. Hence, this study aimed to summarize and compare the dermoscopic feature
Externí odkaz:
https://doaj.org/article/96afad3ca017448fbbc3a97accab9ebc
Autor:
Xue Wang, Yangxue Fu, Yan Liu, Wenjia Nie, Xingyu Su, Xianbiao Zou, Rusong Meng, Yan Li, Juan Tao, Lishao Guo
Publikováno v:
Chinese Medical Journal, Vol 135, Iss 21, Pp 2535-2537 (2022)
Externí odkaz:
https://doaj.org/article/138645285e694db9a0497adb5b7b3fb2
Autor:
Chengxu Li, Wenmin Fei, Yang Han, Xiaoli Ning, Ziyi Wang, Keke Li, Ke Xue, Jingkai Xu, Ruixing Yu, Rusong Meng, Feng Xu, Weimin Ma, Yong Cui
Publikováno v:
Intelligent Medicine, Vol 1, Iss 2, Pp 56-60 (2021)
After more than 60 years of development, artificial intelligence (AI) has been widely used in various fields. Especially in recent years, with the development of deep learning, AI has made many remarkable achievements in the medical field. Dermatolog
Externí odkaz:
https://doaj.org/article/bfd33ecd50f7412aa8541310b3dfd8f6
Autor:
Zexing Song, Yifei Wang, Rusong Meng, Zhenyuan Chen, Yaoying Gao, Xiangjie An, Jing Yang, Yue Yin, Liuqing Chen, Linlin Xin, Ying Xia, Juan Tao, Liu Yang
Publikováno v:
Archives of Dermatological Research.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d940d2d00497493338aa775bcf8218d3
https://doi.org/10.1007/s00403-023-02556-y
https://doi.org/10.1007/s00403-023-02556-y
Publikováno v:
IEEE Transactions on Biomedical Engineering. 63:1248-1256
Goal: Dermoscopy images often suffer from blur and uneven illumination distortions that occur during acquisition, which can adversely influence consequent automatic image analysis results on potential lesion objects. The purpose of this paper is to d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::995e65aca5a6353e6721d4189143ce85
https://doi.org/10.1109/tbme.2015.2493580
https://doi.org/10.1109/tbme.2015.2493580
Publikováno v:
Frontiers of Computer Science. 9:720-728
Segmentation accuracy of dermoscopy images is important in the computer-aided diagnosis of skin cancer and a wide variety of segmentation methods for dermoscopy images have been developed. Considering that each method has its strengths and weaknesses
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c151d696977f0d157417cc8d46e7f63
https://doi.org/10.1007/s11704-015-4391-8
https://doi.org/10.1007/s11704-015-4391-8
Publikováno v:
IEEE Signal Processing Letters. 22:534-538
For the dermoscopy image, uneven illumination will influence segmentation accuracy and lead to wrong aided diagnosis result. In this paper, a no reference uneven illumination assessment metric is proposed for dermoscopy images. Firstly, the distorted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77ebbc058252db7304b58636a9043635
https://doi.org/10.1109/lsp.2014.2357015
https://doi.org/10.1109/lsp.2014.2357015
Publikováno v:
Computers in Biology and Medicine. 59:106-115
The presence of hair is a common quality problem for dermoscopy images, which may influence the accuracy of lesion analysis. In this paper, a novel no-reference hair occlusion assessment method is proposed according to the distribution feature of hai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed03b5ddcfe767ce29ee4e7d21b8fc3b
https://doi.org/10.1016/j.compbiomed.2015.01.023
https://doi.org/10.1016/j.compbiomed.2015.01.023
Publikováno v:
IEEE transactions on medical imaging. 36(3)
We develop a novel method for classifying melanocytic tumors as benign or malignant by the analysis of digital dermoscopy images. The algorithm follows three steps: first, lesions are extracted using a self-generating neural network (SGNN); second, f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ea341a3721720e29abde2b05b08004a
https://pubmed.ncbi.nlm.nih.gov/27913337
https://pubmed.ncbi.nlm.nih.gov/27913337
Publikováno v:
2016 IEEE 13th International Conference on Signal Processing (ICSP).
Dermoscopy images usually suffer from spatially-varying defocus blur, which will easily influence the lesion analysis result and lead to wrong aided diagnosis. In this paper, a novel blind deblurring framework is proposed for dermoscopy images with s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b86ec9f7f205bba32f9c9a8bcea4ad5d
https://doi.org/10.1109/icsp.2016.7877786
https://doi.org/10.1109/icsp.2016.7877786