no code implementations • 12 Feb 2024 • Shiyi Wang, Yang Nan, Felder Federico N, Sheng Zhang, Walsh Simon L F, Guang Yang
The most popular algorithms in medical segmentation, 3D U-Net and its variants, can directly implement the task of lung trachea segmentation, but its failure to consider the special tree-like structure of the trachea suggests that there is much room for improvement in its segmentation accuracy.
no code implementations • 21 Dec 2023 • Yang Nan, Xiaodan Xing, Shiyi Wang, Zeyu Tang, Federico N Felder, Sheng Zhang, Roberta Eufrasia Ledda, Xiaoliu Ding, Ruiqi Yu, Weiping Liu, Feng Shi, Tianyang Sun, Zehong Cao, Minghui Zhang, Yun Gu, Hanxiao Zhang, Jian Gao, Pingyu Wang, Wen Tang, Pengxin Yu, Han Kang, Junqiang Chen, Xing Lu, Boyu Zhang, Michail Mamalakis, Francesco Prinzi, Gianluca Carlini, Lisa Cuneo, Abhirup Banerjee, Zhaohu Xing, Lei Zhu, Zacharia Mesbah, Dhruv Jain, Tsiry Mayet, Hongyu Yuan, Qing Lyu, Abdul Qayyum, Moona Mazher, Athol Wells, Simon LF Walsh, Guang Yang
The online validation set incorporated 52 HRCT scans from patients with fibrotic lung disease and the offline test set included 140 cases from fibrosis and COVID-19 patients.
no code implementations • 9 Oct 2023 • Shiyi Wang, Yang Nan, Simon Walsh, Guang Yang
We propose a novel Deep Active Learning (DeepAL) model-3D Wasserstein Discriminative UNet (WD-UNet) for reducing the annotation effort of medical 3D Computed Tomography (CT) segmentation.
no code implementations • 24 Sep 2023 • Yingying Fang, Xiaodan Xing, Shiyi Wang, Simon Walsh, Guang Yang
Since the onset of the COVID-19 pandemic in 2019, there has been a concerted effort to develop cost-effective, non-invasive, and rapid AI-based tools.
no code implementations • 4 Aug 2022 • Shiyi Wang, Guang Yang
Medical image classification and segmentation based on deep learning (DL) are emergency research topics for diagnosing variant viruses of the current COVID-19 situation.
no code implementations • 5 Jul 2021 • Ivan Guo, Gregoire Loeper, Jan Obloj, Shiyi Wang
We provide a survey of recent results on model calibration by Optimal Transport.
1 code implementation • CVPR 2020 • Yong-Lu Li, Xinpeng Liu, Han Lu, Shiyi Wang, Junqi Liu, Jiefeng Li, Cewu Lu
In light of these, we propose a detailed 2D-3D joint representation learning method.
Ranked #1 on Human-Object Interaction Detection on Ambiguious-HOI
no code implementations • 5 Apr 2020 • Ivan Guo, Gregoire Loeper, Jan Obloj, Shiyi Wang
This paper addresses the joint calibration problem of SPX options and VIX options or futures.
2 code implementations • CVPR 2020 • Yong-Lu Li, Liang Xu, Xinpeng Liu, Xijie Huang, Yue Xu, Shiyi Wang, Hao-Shu Fang, Ze Ma, Mingyang Chen, Cewu Lu
In light of this, we propose a new path: infer human part states first and then reason out the activities based on part-level semantics.
Ranked #3 on Human-Object Interaction Detection on HICO
no code implementations • 15 Jun 2019 • Ivan Guo, Gregoire Loeper, Shiyi Wang
In this paper, we study a semi-martingale optimal transport problem and its application to the calibration of Local-Stochastic Volatility (LSV) models.
4 code implementations • 13 Apr 2019 • Yong-Lu Li, Liang Xu, Xinpeng Liu, Xijie Huang, Yue Xu, Mingyang Chen, Ze Ma, Shiyi Wang, Hao-Shu Fang, Cewu Lu
To address these and promote the activity understanding, we build a large-scale Human Activity Knowledge Engine (HAKE) based on the human body part states.
Ranked #2 on Human-Object Interaction Detection on HICO (using extra training data)