no code implementations • 8 Nov 2022 • Andrew Stamper, Abhinav Singh, James McCouat, Irina Voiculescu
Developmental dysplasia of the hip (DDH) is a condition in infants where the femoral head is incorrectly located in the hip joint.
2 code implementations • 12 Aug 2022 • Ziyang Wang, Irina Voiculescu
The confidence of each model gets improved through the other two views of the feature learning.
no code implementations • 30 Jun 2022 • Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu
In the second stage, the decentralized partially labeled data are exploited to learn an energy-based multi-label classifier for the common classes.
no code implementations • 19 Apr 2022 • Nanqing Dong, Jiayi Wang, Irina Voiculescu
Due to the high human cost of annotation, it is non-trivial to curate a large-scale medical dataset that is fully labeled for all classes of interest.
1 code implementation • CVPR 2022 • James McCouat, Irina Voiculescu
We find that this method not only achieves localisation results on par with other state-of-the-art methods but also an uncertainty score which correlates with the true error for each landmark thereby bringing an overall step change in what a generic computer vision method for landmark detection should be capable of.
no code implementations • 15 Sep 2021 • Nanqing Dong, Irina Voiculescu
A label-efficient paradigm in computer vision is based on self-supervised contrastive pre-training on unlabeled data followed by fine-tuning with a small number of labels.
1 code implementation • 20 May 2021 • Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric Xing
In this work, we provide some theoretical insight into the properties of QNNs by presenting and analyzing a new form of invariance embedded in QNNs for both quantum binary classification and quantum representation learning, which we term negational symmetry.
no code implementations • 9 Mar 2021 • Ziyang Wang, Irina Voiculescu
COVID-19, a new strain of coronavirus disease, has been one of the most serious and infectious disease in the world.
no code implementations • 28 Nov 2020 • Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing
To bridge the methodological gaps in partially supervised learning (PSL) under data scarcity, we propose Vicinal Labels Under Uncertainty (VLUU), a simple yet efficient framework utilizing the human structure similarity for partially supervised medical image segmentation.
no code implementations • 12 Oct 2020 • Sharib Ali, Mariia Dmitrieva, Noha Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Le Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James East, Jens Rittscher
The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies.
no code implementations • 27 Sep 2020 • Ziyang Wang, Zhengdong Zhang, Irina Voiculescu
Segmentation algorithms for medical images are widely studied for various clinical and research purposes.