Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Feng, Youdan"'
The escalating global cancer burden underscores the critical need for precise diagnostic tools in oncology. This research employs deep learning to enhance lesion segmentation in PET/CT imaging, utilizing a dataset of 900 whole-body FDG-PET/CT and 600
Externí odkaz:
http://arxiv.org/abs/2409.09784
This study explores a workflow for automated segmentation of lesions in FDG and PSMA PET/CT images. Due to the substantial differences in image characteristics between FDG and PSMA, specialized preprocessing steps are required. Utilizing YOLOv8 for d
Externí odkaz:
http://arxiv.org/abs/2409.09766
Autor:
Zhang, Tianyi, Feng, Youdan, Feng, Yunlu, Zhao, Yu, Lei, Yanli, Ying, Nan, Yan, Zhiling, He, Yufang, Zhang, Guanglei
The rapid on-site evaluation (ROSE) technique can signifi-cantly accelerate the diagnosis of pancreatic cancer by im-mediately analyzing the fast-stained cytopathological images. Computer-aided diagnosis (CAD) can potentially address the shortage of
Externí odkaz:
http://arxiv.org/abs/2208.06833
The rapid on-site evaluation (ROSE) technique can significantly ac-celerate the diagnostic workflow of pancreatic cancer by immediately analyzing the fast-stained cytopathological images with on-site pathologists. Computer-aided diagnosis (CAD) using
Externí odkaz:
http://arxiv.org/abs/2206.03080
Autor:
Zhang, Tianyi, Feng, Yunlu, Zhao, Yu, Fan, Guangda, Yang, Aiming, Lyu, Shangqin, Zhang, Peng, Song, Fan, Ma, Chenbin, Sun, Yangyang, Feng, Youdan, Zhang, Guanglei
Pancreatic cancer is one of the most malignant cancers in the world, which deteriorates rapidly with very high mortality. The rapid on-site evaluation (ROSE) technique innovates the workflow by immediately analyzing the fast stained cytopathological
Externí odkaz:
http://arxiv.org/abs/2112.13513
Autor:
Zhao, Xiangyu, Zhang, Peng, Song, Fan, Ma, Chenbin, Fan, Guangda, Sun, Yangyang, Feng, Youdan, Zhang, Guanglei
The accurate segmentation of multiple types of lesions from adjacent tissues in medical images is significant in clinical practice. Convolutional neural networks (CNNs) based on the coarse-to-fine strategy have been widely used in this field. However
Externí odkaz:
http://arxiv.org/abs/2110.04735
Autor:
Zhang, Tianyi, Feng, Youdan, Zhao, Yu, Lei, Yanli, Ying, Nan, Song, Fan, He, Yufang, Yan, Zhiling, Feng, Yunlu, Yang, Aiming, Zhang, Guanglei
Publikováno v:
In Computer Methods and Programs in Biomedicine February 2024 244
Autor:
He, Yufang, Song, Fan, Wu, Wangjiang, Tian, Suqing, Zhang, Tianyi, Zhang, Shuming, Zhang, Peng, Ma, Chenbin, Feng, Youdan, Yang, Ruijie, Zhang, Guanglei
Publikováno v:
In Medicine in Novel Technology and Devices June 2023 18
Autor:
Zhang, Peng, Ma, Chenbin, Song, Fan, Zhang, Tianyi, Sun, Yangyang, Feng, Youdan, He, Yufang, Liu, Fei, Wang, Daifa, Zhang, Guanglei
Publikováno v:
In Computer Methods and Programs in Biomedicine February 2023 229
Akademický článek
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