Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Shuolin Liu"'
Autor:
Shuolin Liu, Yaguang Bi, Tianting Han, Yiran E. Li, Qihang Wang, Ne Natalie Wu, Chenguo Xu, Junbo Ge, Ronggui Hu, Yingmei Zhang
Publikováno v:
Cell Discovery, Vol 10, Iss 1, Pp 1-23 (2024)
Abstract Inflammasome activation and pyroptotic cell death are known to contribute to the pathogenesis of cardiovascular diseases, such as myocardial ischemia-reperfusion (I/R) injury, although the underlying regulatory mechanisms remain poorly under
Externí odkaz:
https://doaj.org/article/35a8717ca6e747e8af85a8312821f616
Autor:
Yaguang Bi, Shuolin Liu, Xing Qin, Miyesaier Abudureyimu, Lu Wang, Rongjun Zou, Amir Ajoolabady, Wenjing Zhang, Hu Peng, Jun Ren, Yingmei Zhang
Publikováno v:
Journal of Advanced Research, Vol 55, Iss , Pp 45-60 (2024)
Introduction: Liver fibrosis is a life-threatening pathological anomaly which usually evolves into advanced liver cirrhosis and hepatocellular carcinoma although limited therapeutic option is readily available. FUN14 domain containing 1 (FUNDC1) is a
Externí odkaz:
https://doaj.org/article/a2fe01d001a7411dbd62d8473bb71797
Autor:
Yaguang Bi, Shuolin Liu, Xing Qin, Miyesaier Abudureyimu, Lu Wang, Rongjun Zou, Amir Ajoolabady, Wenjing Zhang, Hu Peng, Jun Ren, Yingmei Zhang
Publikováno v:
Journal of Advanced Research.
Autor:
Aaron Babier, Rafid Mahmood, Binghao Zhang, Victor G L Alves, Ana Maria Barragán-Montero, Joel Beaudry, Carlos E Cardenas, Yankui Chang, Zijie Chen, Jaehee Chun, Kelly Diaz, Harold David Eraso, Erik Faustmann, Sibaji Gaj, Skylar Gay, Mary Gronberg, Bingqi Guo, Junjun He, Gerd Heilemann, Sanchit Hira, Yuliang Huang, Fuxin Ji, Dashan Jiang, Jean Carlo Jimenez Giraldo, Hoyeon Lee, Jun Lian, Shuolin Liu, Keng-Chi Liu, José Marrugo, Kentaro Miki, Kunio Nakamura, Tucker Netherton, Dan Nguyen, Hamidreza Nourzadeh, Alexander F I Osman, Zhao Peng, José Darío Quinto Muñoz, Christian Ramsl, Dong Joo Rhee, Juan David Rodriguez, Hongming Shan, Jeffrey V Siebers, Mumtaz H Soomro, Kay Sun, Andrés Usuga Hoyos, Carlos Valderrama, Rob Verbeek, Enpei Wang, Siri Willems, Qi Wu, Xuanang Xu, Sen Yang, Lulin Yuan, Simeng Zhu, Lukas Zimmermann, Kevin L Moore, Thomas G Purdie, Andrea L McNiven, Timothy C Y Chan
Publikováno v:
Physics in medicine and biology. 67(18)
We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients with head-and-neck cancer and high-quality dose predictions from 19 KBP
Autor:
Alexandr G. Rassadin, Ali Asghar Khani, Yinyin Yuan, Neeraj Kumar, Nikhil Cherian Kurian, Hasib Zunair, Hamid Behroozi, Priya Lakshmi Narayanan, Shuolin Liu, Romil Lodaya, Yanling Liu, Dwarikanath Mahapatra, Abhijeet Patil, Lata Kini, Pavel Semkin, Yuehan Yao, Hyun Jung, Seyed Alireza Fatemi Jahromi, Sanjay N. Talbar, Swapnil Rane, Ming Feng, Bhakti Baheti, G Thomas Brown, Vikas Ramachandra, Justin Law, Rupert Ecker, Xiyi Wu, Isabella Ellinger, Prasad Dutande, Tang-Kai Yin, Ehsan Montahaei, Shan E Ahmed Raza, Amirreza Mahbod, Aditya Mitkari, Abdessamad Ben Hamza, Hanyun Zhang, Zhengyu Xu, Kele Xu, Quoc Dang Vu, Yijie Huang, Bin Dong, Shikhar Srivastava, Lisheng Wang, Mahdieh Soleymani Baghshah, Nasir M. Rajpoot, Zhipeng Luo, Shuai Lv, Ujjwal Baid, Huai Chen, Ruchika Verma, Simon Graham, Lubomira Trnavska, Mieke Zwager, Steven Smiley, Amit Sethi, Abhiroop Tejomay, Dinesh Koka, Qi-Rui Fang
Publikováno v:
Ieee transactions on medical imaging, 40(12), 3413-3423. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d246f6bb68a09afa5970571e21e0d90a
https://research.rug.nl/en/publications/4639c9a9-8918-43fd-85fe-8ba1648b51e6
https://research.rug.nl/en/publications/4639c9a9-8918-43fd-85fe-8ba1648b51e6
Publikováno v:
Medical physicsREFERENCES. 48(9)
PURPOSE Although large datasets are available, to learn a robust dose prediction model from a limited dataset still remains challenging. This work employed cascaded deep learning models and advanced training strategies with a limited dataset to preci
Autor:
Shuolin Liu
Publikováno v:
Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19.
Publikováno v:
Artificial Intelligence in Radiation Therapy ISBN: 9783030324858
AIRT@MICCAI
AIRT@MICCAI
Dose volume histogram (DVH) is an important dosimetry evaluation metric and it plays an important role in guiding the development of esophageal ra-diotherapy treatment plans. Automatic DVH prediction is therefore very use-ful to achieve high-quality
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::769f779f16638a44695a2ddd1568a138
https://doi.org/10.1007/978-3-030-32486-5_11
https://doi.org/10.1007/978-3-030-32486-5_11
Publikováno v:
Artificial Intelligence in Radiation Therapy ISBN: 9783030324858
AIRT@MICCAI
AIRT@MICCAI
Radiotherapy treatment planning often demands substantial manual adjustments to achieve maximal dose delivery at the planning target volumes (PTVs) and protecting surrounding organs at risk (OARs). Automatic dose prediction can reduce manual adjustme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35be7dc0e87e9844f9119151ab5b863e
https://doi.org/10.1007/978-3-030-32486-5_9
https://doi.org/10.1007/978-3-030-32486-5_9
Publikováno v:
Physics in Medicine & Biology. 65:205013
This work aims to develop a voxel-level dose prediction framework by integrating distance information between PTV and OARs, as well as image information, into a densely-connected network (DCNN). Firstly, a four-channel feature map, consisting of a PT