1 code implementation • 1 Dec 2022 • Jiajin Zhang, Hanqing Chao, Amit Dhurandhar, Pin-Yu Chen, Ali Tajer, Yangyang Xu, Pingkun Yan
Domain generalization (DG) aims to train a model to perform well in unseen domains under different distributions.
no code implementations • 11 Oct 2022 • Xinrui Song, Xuanang Xu, Sheng Xu, Baris Turkbey, Bradford J. Wood, Thomas Sanford, Pingkun Yan
We then use the predicted landmarks to generate the affine transformation matrix, which outperforms the clinicians' manual rigid registration by a significant margin in terms of TRE.
no code implementations • 4 Oct 2022 • Xi Fang, Daeseung Kim, Xuanang Xu, Tianshu Kuang, Hannah H. Deng, Joshua C. Barber, Nathan Lampen, Jaime Gateno, Michael A. K. Liebschner, James J. Xia, Pingkun Yan
In this work, we propose an Attentive Correspondence assisted Movement Transformation network (ACMT-Net) to estimate the facial appearance by transforming the bony movement to facial soft tissue through a point-to-point attentive correspondence matrix.
1 code implementation • 12 Jul 2022 • Hanqing Chao, Jiajin Zhang, Pingkun Yan
Regression plays an essential role in many medical imaging applications for estimating various clinical risk or measurement scores.
no code implementations • 14 Jun 2022 • Xuanang Xu, Pingkun Yan
Extensive experiments on four public datasets show that our Fed-MENU method can effectively obtain a federated learning model using the partially labeled datasets with superior performance to other models trained by either localized or centralized learning methods.
no code implementations • 5 Apr 2022 • Xuanang Xu, Tianyi Chen, Han Deng, Tianshu Kuang, Joshua C. Barber, Daeseung Kim, Jaime Gateno, Pingkun Yan, James J. Xia
In this paper, we first conduct a theoretical analysis on the FL algorithm to reveal the problem of model aggregation during training on non-iid data.
no code implementations • 24 Mar 2022 • Chuang Niu, Giridhar Dasegowda, Pingkun Yan, Mannudeep K. Kalra, Ge Wang
Although radiographs are the most frequently used worldwide due to their cost-effectiveness and widespread accessibility, the structural superposition along the x-ray paths often renders suspicious or concerning lung nodules difficult to detect.
1 code implementation • 14 Jul 2021 • Hengtao Guo, Xuanang Xu, Sheng Xu, Bradford J. Wood, Pingkun Yan
Fusing intra-operative 2D transrectal ultrasound (TRUS) image with pre-operative 3D magnetic resonance (MR) volume to guide prostate biopsy can significantly increase the yield.
1 code implementation • 9 Jul 2021 • Xinrui Song, Hengtao Guo, Xuanang Xu, Hanqing Chao, Sheng Xu, Baris Turkbey, Bradford J. Wood, Ge Wang, Pingkun Yan
In the past few years, convolutional neural networks (CNNs) have been proved powerful in extracting image features crucial for image registration.
no code implementations • 20 May 2021 • Nkechinyere N. Agu, Joy T. Wu, Hanqing Chao, Ismini Lourentzou, Arjun Sharma, Mehdi Moradi, Pingkun Yan, James Hendler
Radiologists usually observe anatomical regions of chest X-ray images as well as the overall image before making a decision.
1 code implementation • 25 Mar 2021 • Jiajin Zhang, Hanqing Chao, Xuanang Xu, Chuang Niu, Ge Wang, Pingkun Yan
The extensive use of medical CT has raised a public concern over the radiation dose to the patient.
no code implementations • 3 Mar 2021 • Erim Yanik, Xavier Intes, Uwe Kruger, Pingkun Yan, David Miller, Brian Van Voorst, Basiel Makled, Jack Norfleet, Suvranu De
Here, we use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to systematically survey the literature on the use of Deep Neural Networks for automated and objective surgical skill assessment, with a focus on kinematic data as putative markers of surgical competency.
no code implementations • 18 Feb 2021 • Chuang Niu, Ge Wang, Pingkun Yan, Juergen Hahn, Youfang Lai, Xun Jia, Arjun Krishna, Klaus Mueller, Andreu Badal, KyleJ. Myers, Rongping Zeng
We propose a Noise Entangled GAN (NE-GAN) for simulating low-dose computed tomography (CT) images from a higher dose CT image.
no code implementations • 18 Nov 2020 • Jiajin Zhang, Hanqing Chao, Pingkun Yan
Unsupervised domain adaptation (UDA) is widely used to transfer knowledge from a labeled source domain to an unlabeled target domain with different data distribution.
no code implementations • 17 Nov 2020 • Hengtao Guo, Sheng Xu, Bradford J. Wood, Pingkun Yan
However, such algorithms are specific to particular transducers and scanning trajectories associated with the training data, which may not be generalized to other image acquisition settings.
2 code implementations • 16 Aug 2020 • Hanqing Chao, Hongming Shan, Fatemeh Homayounieh, Ramandeep Singh, Ruhani Doda Khera, Hengtao Guo, Timothy Su, Ge Wang, Mannudeep K. Kalra, Pingkun Yan
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population.
no code implementations • 4 Aug 2020 • Weiwen Wu, Dianlin Hu, Wenxiang Cong, Hongming Shan, Shao-Yu Wang, Chuang Niu, Pingkun Yan, Hengyong Yu, Varut Vardhanabhuti, Ge Wang
ACID synergizes a deep reconstruction network trained on big data, kernel awareness from CS-inspired processing, and iterative refinement to minimize the data residual relative to real measurement.
1 code implementation • 20 Jul 2020 • Hanqing Chao, Xi Fang, Jiajin Zhang, Fatemeh Homayounieh, Chiara D. Arru, Subba R. Digumarthy, Rosa Babaei, Hadi K. Mobin, Iman Mohseni, Luca Saba, Alessandro Carriero, Zeno Falaschi, Alessio Pasche, Ge Wang, Mannudeep K. Kalra, Pingkun Yan
Management of high-risk patients with early intervention is a key to lower the fatality rate of COVID-19 pneumonia, as a majority of patients recover naturally.
1 code implementation • 13 Jun 2020 • Hengtao Guo, Sheng Xu, Bradford Wood, Pingkun Yan
Transrectal ultrasound (US) is the most commonly used imaging modality to guide prostate biopsy and its 3D volume provides even richer context information.
1 code implementation • 3 Jun 2020 • Qikui Zhu, Bo Du, Pingkun Yan
Furthermore, the adjacency matrix is usually pre-defined and stationary, which makes the data augmentation strategies cannot be employed on the constructed graph structures data to augment the amount of training data.
1 code implementation • 1 Jan 2020 • Xi Fang, Pingkun Yan
Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem becomes more pronounced in multi-organ segmentation.
no code implementations • 5 Dec 2019 • Qikui Zhu, Bo Du, Pingkun Yan
Furthermore, instead of using image based similarity for label fusion, which can be distracted by the large background areas, we propose a novel strategy to compute the label similarity based weights for label fusion.
1 code implementation • 12 Nov 2019 • Qikui Zhu, Bo Du, Pingkun Yan
To address the above weaknesses, in this paper, we propose a new method of multi-hop convolutional network on weighted graphs.
no code implementations • 24 Oct 2019 • Xi Fang, Bo Du, Sheng Xu, Bradford J. Wood, Pingkun Yan
Automatic medical image segmentation, an essential component of medical image analysis, plays an importantrole in computer-aided diagnosis.
no code implementations • 28 Mar 2019 • Xueying Chen, Rong Zhang, Pingkun Yan
Liver lesion segmentation is a difficult yet critical task for medical image analysis.
no code implementations • 5 Mar 2019 • Grant Haskins, Uwe Kruger, Pingkun Yan
This survey, therefore, outlines the evolution of deep learning based medical image registration in the context of both research challenges and relevant innovations in the past few years.
1 code implementation • 21 Feb 2019 • Qikui Zhu, Bo Du, Pingkun Yan
To make the network more sensitive to the boundaries during segmentation, a boundary-weighted segmentation loss (BWL) is proposed.
1 code implementation • 20 Feb 2019 • Hengtao Guo, Uwe Kruger, Ge Wang, Mannudeep K. Kalra, Pingkun Yan
Recent studies have highlighted the high correlation between cardiovascular diseases (CVD) and lung cancer, and both are associated with significant morbidity and mortality.
1 code implementation • 22 Nov 2018 • Fenglei Fan, Dayang Wang, Hengtao Guo, Qikui Zhu, Pingkun Yan, Ge Wang, Hengyong Yu
In this paper, we investigate the expressivity and generalizability of a novel sparse shortcut topology.
no code implementations • 19 Oct 2018 • Pingkun Yan, Hengtao Guo, Ge Wang, Ruben De Man, Mannudeep K. Kalra
In this paper, we propose a deep learning based method, which takes both chest LDCT image patches and coronary artery calcification risk scores as input, for direct prediction of mortality risk of lung cancer subjects.
no code implementations • 12 Jun 2018 • Grant Haskins, Jochen Kruecker, Uwe Kruger, Sheng Xu, Peter A. Pinto, Brad J. Wood, Pingkun Yan
Conclusion: A similarity metric that is learned using a deep neural network can be used to assess the quality of any given image registration and can be used in conjunction with the aforementioned optimization framework to perform automatic registration that is robust to poor initialization.
no code implementations • 30 Apr 2018 • Pingkun Yan, Sheng Xu, Ardeshir R. Rastinehad, Brad J. Wood
Robust and accurate alignment of multimodal medical images is a very challenging task, which however is very useful for many clinical applications.
9 code implementations • 3 Aug 2017 • Qingsong Yang, Pingkun Yan, Yanbo Zhang, Hengyong Yu, Yongyi Shi, Xuanqin Mou, Mannudeep K. Kalra, Ge Wang
In this paper, we introduce a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity.
no code implementations • 22 Mar 2017 • Qikui Zhu, Bo Du, Baris Turkbey, Peter L . Choyke, Pingkun Yan
Prostate segmentation from Magnetic Resonance (MR) images plays an important role in image guided interven- tion.
no code implementations • 22 Feb 2017 • Qingsong Yang, Pingkun Yan, Mannudeep K. Kalra, Ge Wang
Reduction of radiation dose associated with CT can increase noise and artifacts, which can adversely affect diagnostic confidence.