Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Jiatai Lin"'
Autor:
Xipeng Pan, Huan Lin, Chu Han, Zhengyun Feng, Yumeng Wang, Jiatai Lin, Bingjiang Qiu, Lixu Yan, Bingbing Li, Zeyan Xu, Zhizhen Wang, Ke Zhao, Zhenbing Liu, Changhong Liang, Xin Chen, Zhenhui Li, Yanfen Cui, Cheng Lu, Zaiyi Liu
Publikováno v:
iScience, Vol 25, Iss 12, Pp 105605- (2022)
Summary: A high abundance of tumor-infiltrating lymphocytes (TILs) has a positive impact on the prognosis of patients with lung adenocarcinoma (LUAD). We aimed to develop and validate an artificial intelligence-driven pathological scoring system for
Externí odkaz:
https://doaj.org/article/a1af3ef1e5064736b8f016797a9708d0
Publikováno v:
IEEE Access, Vol 8, Pp 157391-157402 (2020)
Almost all successful nodule detectors rely heavily on a fixed set of anchor boxes. In this paper, inspired by the success of the keypoint estimation method in natural image detection, we propose an anchor-free framework for accurate pulmonary nodule
Externí odkaz:
https://doaj.org/article/89f123055c164e7890b8e7c931407b96
Autor:
Jiatai Lin, Guoqiang Han, Xipeng Pan, Zaiyi Liu, Hao Chen, Danyi Li, Xiping Jia, Zhenwei Shi, Zhizhen Wang, Yanfen Cui, Haiming Li, Changhong Liang, Li Liang, Ying Wang, Chu Han
Publikováno v:
IEEE Transactions on Medical Imaging. 41:2252-2262
Histopathological tissue classification is a simpler way to achieve semantic segmentation for the whole slide images, which can alleviate the requirement of pixel-level dense annotations. Existing works mostly leverage the popular CNN classification
Autor:
Jianwei Lin, Jiatai Lin, Cheng Lu, Hao Chen, Huan Lin, Bingchao Zhao, Zhenwei Shi, Bingjiang Qiu, Xipeng Pan, Zeyan Xu, Biao Huang, Changhong Liang, Guoqiang Han, Zaiyi Liu, Chu Han
Brain tumor segmentation (BTS) in magnetic resonance image (MRI) is crucial for brain tumor diagnosis, cancer management and research purposes. With the great success of the ten-year BraTS challenges as well as the advances of CNN and Transformer alg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2ae6fe290fd6eefa4cb41366bae941e
http://arxiv.org/abs/2207.07370
http://arxiv.org/abs/2207.07370
Publikováno v:
IEEE Access, Vol 8, Pp 157391-157402 (2020)
Almost all successful nodule detectors rely heavily on a fixed set of anchor boxes. In this paper, inspired by the success of the keypoint estimation method in natural image detection, we propose an anchor-free framework for accurate pulmonary nodule
Autor:
Yuhao Mo, Chu Han, Yu Liu, Min Liu, Zhenwei Shi, Jiatai Lin, Bingchao Zhao, Chunwang Huang, Bingjiang Qiu, Yanfen Cui, Lei Wu, Xipeng Pan, Zeyan Xu, Xiaomei Huang, Zhenhui Li, Zaiyi Liu, Ying Wang, Changhong Liang
Publikováno v:
IEEE Transactions on Medical Imaging. :1-1
Autor:
Bingchao Zhao, Chu Han, Xipeng Pan, Jiatai Lin, Zongjian Yi, Changhong Liang, Xin Chen, Bingbing Li, Weihao Qiu, Danyi Li, Li Liang, Ying Wang, Zaiyi Liu
Publikováno v:
Computers and Electrical Engineering. 103:108304
Autor:
Chu Han, Jiatai Lin, Jinhai Mai, Yi Wang, Qingling Zhang, Bingchao Zhao, Xin Chen, Xipeng Pan, Zhenwei Shi, Zeyan Xu, Su Yao, Lixu Yan, Huan Lin, Xiaomei Huang, Changhong Liang, Guoqiang Han, Zaiyi Liu
Publikováno v:
Medical Image Analysis. 80:102487
Tissue-level semantic segmentation is a vital step in computational pathology. Fully-supervised models have already achieved outstanding performance with dense pixel-level annotations. However, drawing such labels on the giga-pixel whole slide images
Publikováno v:
2019 Chinese Automation Congress (CAC).
In the Visual Simultaneous Localization and Mapping (V-SLAM) system, loop closure detection is playing a decisive role in the accurate construction of maps. Traditional loop closure detection mainly use the Bag-of-Words (BoW) model to extract feature
Publikováno v:
2019 Chinese Automation Congress (CAC).
Gestures recognition plays an important role in the robot systems, which can change existing human-computer interaction. In the existing researches, surface electromyography(sEMG) signals are widely used to classify and recognize gestures. However, t