no code implementations • 4 Dec 2023 • Longhui Yuan, Shuang Li, Zhuo He, Binhui Xie
Extensive experiments demonstrate that ATASeg bridges the performance gap between TTA methods and their supervised counterparts with only extremely few annotations, even one click for labeling surpasses known SOTA TTA methods by 2. 6% average mIoU on ACDC benchmark.
no code implementations • 2 Jun 2023 • Zhuo He, Hongjin Si, Xinwei Zhang, Qing-Hui Chen, Jiangang Zou, Weihua Zhou
The model was fine-tuned to extract relevant features from the ECG images, and then tested on our dataset of CRT patients to predict their response.
no code implementations • 4 May 2023 • Kristoffer Larsena, Zhuo He, Chen Zhao, Xinwei Zhang, Quiying Sha, Claudio T Mesquitad, Diana Paeze, Ernest V. Garciaf, Jiangang Zou, Amalia Peix, Weihua Zhou
The DL model outperformed the ML models, showcasing the additional predictive benefit of utilizing SPECT MPI polarmaps.
no code implementations • 7 Aug 2022 • Fubao Zhu, Guojie Wang, Chen Zhao, Saurabh Malhotra, Min Zhao, Zhuo He, Jianzhou Shi, Zhixin Jiang, Weihua Zhou
Five-fold cross-validation with 180 stress and 201 rest MPIs was used for training and internal validation; the remaining images were used for testing.
1 code implementation • 11 Oct 2021 • Chen Zhao, Shi Shi, Zhuo He, Cheng Wang, Zhongqiang Zhao, Xinli Li, Yanli Zhou, Weihua Zhou
By integrating the spatial features from each cardiac frame of the gated MPS and the temporal features from the sequential cardiac frames of the gated MPS, we developed a Spatial-Temporal V-Net (ST-VNet) for automatic extraction of RV endocardial and epicardial contours.
no code implementations • 1 Jun 2021 • Zhuo He, Xinwei Zhang, Chen Zhao, Zhiyong Qian, Yao Wang, Xiaofeng Hou, Jiangang Zou, Weihua Zhou
Correlation analysis was used to explain the relationships between new parameters with conventional LVMD parameters.
no code implementations • 25 Jan 2021 • Chen Zhao, Haipeng Tang, Daniel McGonigle, Zhuo He, Chaoyang Zhang, Yu-Ping Wang, Hong-Wen Deng, Robert Bober, Weihua Zhou
We aim to develop an automatic algorithm by deep learning to extract coronary arteries from ICAs. In this study, a multi-input and multi-scale (MIMS) U-Net with a two-stage recurrent training strategy was proposed for the automatic vessel segmentation.
no code implementations • 20 Jun 2020 • Xuan Hua, Jungang Han, Chen Zhao, Haipeng Tang, Zhuo He, Jinshan Tang, Qing-Hui Chen, Shaojie Tang, Weihua Zhou
This paper presents an end-to-end ECG signal classification method based on a novel segmentation strategy via 1D Convolutional Neural Networks (CNN) to aid the classification of ECG signals.