Youbao Tang

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National Institutes of Health ∙ Harbin Institute of Technology

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One Click Lesion RECIST Measurement and Segmentation on CT Scans

In clinical trials, one of the radiologists' routine work is to measure ...
07/21/2020 ∙ by Youbao Tang, et al. ∙ 0 ∙ share

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E^2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans

Developing an effective liver and liver tumor segmentation model from CT...
07/19/2020 ∙ by Youbao Tang, et al. ∙ 0 ∙ share

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Cross-Domain Medical Image Translation by Shared Latent Gaussian Mixture Model

Current deep learning based segmentation models often generalize poorly ...
07/14/2020 ∙ by Yingying Zhu, et al. ∙ 1 ∙ share

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Bone Suppression on Chest Radiographs With Adversarial Learning

Dual-energy (DE) chest radiography provides the capability of selectivel...
02/08/2020 ∙ by Jia Liang, et al. ∙ 0 ∙ share

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Weakly Supervised Lesion Co-segmentation on CT Scans

Lesion segmentation in medical imaging serves as an effective tool for a...
01/24/2020 ∙ by Vatsal Agarwal, et al. ∙ 18 ∙ share

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Weakly-Supervised Lesion Segmentation on CT Scans using Co-Segmentation

Lesion segmentation on computed tomography (CT) scans is an important st...
01/23/2020 ∙ by Vatsal Agarwal, et al. ∙ 8 ∙ share

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TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays

In this work, we exploit the unsupervised domain adaptation problem for ...
08/21/2019 ∙ by Yuxing Tang, et al. ∙ 0 ∙ share

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MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

When reading medical images such as a computed tomography (CT) scan, rad...
08/12/2019 ∙ by Ke Yan, et al. ∙ 6 ∙ share

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XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation

This paper proposes a novel framework for lung segmentation in chest X-r...
04/19/2019 ∙ by Youbao Tang, et al. ∙ 0 ∙ share

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Abnormal Chest X-ray Identification With Generative Adversarial One-Class Classifier

Being one of the most common diagnostic imaging tests, chest radiography...
03/05/2019 ∙ by Yuxing Tang, et al. ∙ 0 ∙ share

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ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining

Automatic lesion detection from computed tomography (CT) scans is an imp...
01/18/2019 ∙ by Youbao Tang, et al. ∙ 2 ∙ share

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CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

Automated lesion segmentation from computed tomography (CT) is an import...
07/18/2018 ∙ by Youbao Tang, et al. ∙ 0 ∙ share

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Accurate Weakly-Supervised Deep Lesion Segmentation using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST

Volumetric lesion segmentation from computed tomography (CT) images is a...
07/02/2018 ∙ by Jinzheng Cai, et al. ∙ 0 ∙ share

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Semi-Automatic RECIST Labeling on CT Scans with Cascaded Convolutional Neural Networks

Response evaluation criteria in solid tumors (RECIST) is the standard me...
06/25/2018 ∙ by Youbao Tang, et al. ∙ 6 ∙ share

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CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation

Data availability plays a critical role for the performance of deep lear...
06/11/2018 ∙ by Dakai Jin, et al. ∙ 2 ∙ share

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Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST

Volumetric lesion segmentation via medical imaging is a powerful means t...
01/25/2018 ∙ by Jinzheng Cai, et al. ∙ 0 ∙ share

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Saliency Detection via Combining Region-Level and Pixel-Level Predictions with CNNs

This paper proposes a novel saliency detection method by combining regio...
08/18/2016 ∙ by Youbao Tang, et al. ∙ 0 ∙ share

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Deeply-Supervised Recurrent Convolutional Neural Network for Saliency Detection

This paper proposes a novel saliency detection method by developing a de...
08/18/2016 ∙ by Youbao Tang, et al. ∙ 0 ∙ share

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