Zobrazeno 1 - 10
of 366
pro vyhledávání: '"Liu, Zelong"'
Medical anomaly detection is a critical research area aimed at recognizing abnormal images to aid in diagnosis.Most existing methods adopt synthetic anomalies and image restoration on normal samples to detect anomaly. The unlabeled data consisting of
Externí odkaz:
http://arxiv.org/abs/2405.12872
Autor:
Liu, Zelong, Tieu, Andrew, Patel, Nikhil, Zhou, Alexander, Soultanidis, George, Fayad, Zahi A., Deyer, Timothy, Mei, Xueyan
Artificial Intelligence (AI) has the potential to revolutionize diagnosis and segmentation in medical imaging. However, development and clinical implementation face multiple challenges including limited data availability, lack of generalizability, an
Externí odkaz:
http://arxiv.org/abs/2402.01034
Autor:
Zhou, Alexander, Liu, Zelong, Tieu, Andrew, Patel, Nikhil, Sun, Sean, Yang, Anthony, Choi, Peter, Fauveau, Valentin, Soultanidis, George, Huang, Mingqian, Doshi, Amish, Fayad, Zahi A., Deyer, Timothy, Mei, Xueyan
Purpose To develop a deep learning model for multi-anatomy and many-class segmentation of diverse anatomic structures on MRI imaging. Materials and Methods In this retrospective study, two datasets were curated and annotated for model development and
Externí odkaz:
http://arxiv.org/abs/2402.01031
Autor:
Liu, Zelong, Zhou, Alexander, Yang, Arnold, Yilmaz, Alara, Yoo, Maxwell, Sullivan, Mikey, Zhang, Catherine, Grant, James, Li, Daiqing, Fayad, Zahi A., Huver, Sean, Deyer, Timothy, Mei, Xueyan
Deep learning in medical imaging often requires large-scale, high-quality data or initiation with suitably pre-trained weights. However, medical datasets are limited by data availability, domain-specific knowledge, and privacy concerns, and the creat
Externí odkaz:
http://arxiv.org/abs/2312.05953
Autor:
Pinaya, Walter H. L., Graham, Mark S., Kerfoot, Eric, Tudosiu, Petru-Daniel, Dafflon, Jessica, Fernandez, Virginia, Sanchez, Pedro, Wolleb, Julia, da Costa, Pedro F., Patel, Ashay, Chung, Hyungjin, Zhao, Can, Peng, Wei, Liu, Zelong, Mei, Xueyan, Lucena, Oeslle, Ye, Jong Chul, Tsaftaris, Sotirios A., Dogra, Prerna, Feng, Andrew, Modat, Marc, Nachev, Parashkev, Ourselin, Sebastien, Cardoso, M. Jorge
Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to help safely share medical data via synthetic datasets but also to perfor
Externí odkaz:
http://arxiv.org/abs/2307.15208
Publikováno v:
In Journal of Cereal Science September 2024 119
Publikováno v:
In Measurement 15 January 2025 239
Publikováno v:
In Energy 1 December 2024 311
One of the key problems in multi-label text classification is how to take advantage of the correlation among labels. However, it is very challenging to directly model the correlations among labels in a complex and unknown label space. In this paper,
Externí odkaz:
http://arxiv.org/abs/2106.10076
Publikováno v:
In Food Chemistry 15 January 2024 431