2 code implementations • 7 Sep 2021 • Hong-Yu Zhou, Jiansen Guo, Yinghao Zhang, Lequan Yu, Liansheng Wang, Yizhou Yu
Transformer, the model of choice for natural language processing, has drawn scant attention from the medical imaging community.
Ranked #1 on Medical Image Segmentation on Synapse
1 code implementation • 4 Nov 2021 • Hong-Yu Zhou, Xiaoyu Chen, Yinghao Zhang, Ruibang Luo, Liansheng Wang, Yizhou Yu
Pre-training lays the foundation for recent successes in radiograph analysis supported by deep learning.
no code implementations • 2 Jun 2022 • Yinghao Zhang, Peng Li, Yue Hu
While low-rank matrix prior has been exploited in dynamic MR image reconstruction and has obtained satisfying performance, tensor low-rank models have recently emerged as powerful alternative representations for three-dimensional dynamic MR datasets.
1 code implementation • 2 Jun 2022 • Yinghao Zhang, Yue Hu
Recently, a new tensor nuclear norm based on t-SVD has been proposed and applied to tensor completion.
1 code implementation • 8 Sep 2022 • Yinghao Zhang, Yue Hu
By generalizing the FFT into an arbitrary unitary transformation of the transformed t-SVD and proposing the transformed tensor nuclear norm (TTNN), we introduce a flexible model based on TTNN with the ability to exploit the tensor low-rank prior of a transformed domain in a larger transformation space and elaborately design an iterative optimization algorithm based on the alternating direction method of multipliers (ADMM), which is further unrolled into a model-based deep unrolling reconstruction network to learn the transformed tensor low-rank prior (T$^2$LR-Net).
no code implementations • 14 Sep 2022 • Zesong Qiu, Yuwei Li, Dongming He, Qixuan Zhang, Longwen Zhang, Yinghao Zhang, Jingya Wang, Lan Xu, Xudong Wang, Yuyao Zhang, Jingyi Yu
Named after the fossils of one of the oldest known human ancestors, our LUCY dataset contains high-quality Computed Tomography (CT) scans of the complete human head before and after orthognathic surgeries, critical for evaluating surgery results.
1 code implementation • 19 Jul 2023 • Yinghao Zhang, Xiaodi Li, Weihang Li, Yue Hu
In particular, we put forward a novel deep unrolling shrinkage network (DUS-Net) by unrolling the alternating direction method of multipliers (ADMM) for optimizing the transformed $l_1$ norm dynamic MR reconstruction model.
no code implementations • 8 Dec 2023 • Debo Cheng, Yang Xie, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu, Yinghao Zhang, Zaiwen Feng
To address this problem with co-occurring M-bias and confounding bias, we propose a novel Disentangled Latent Representation learning framework for learning latent representations from proxy variables for unbiased Causal effect Estimation (DLRCE) from observational data.