Search Results for author: YouBao Tang

Found 16 papers, 4 papers with code

A Flexible Three-Dimensional Hetero-phase Computed Tomography Hepatocellular Carcinoma (HCC) Detection Algorithm for Generalizable and Practical HCC Screening

no code implementations17 Aug 2021 Chi-Tung Cheng, Jinzheng Cai, Wei Teng, Youjing Zheng, YuTing Huang, Yu-Chao Wang, Chien-Wei Peng, YouBao Tang, Wei-Chen Lee, Ta-Sen Yeh, Jing Xiao, Le Lu, Chien-Hung Liao, Adam P. Harrison

We develop a flexible three-dimensional deep algorithm, called hetero-phase volumetric detection (HPVD), that can accept any combination of contrast-phase inputs and with adjustable sensitivity depending on the clinical purpose.

Computed Tomography (CT)

Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection

no code implementations5 May 2021 YouBao Tang, Ke Yan, Jinzheng Cai, Lingyun Huang, Guotong Xie, Jing Xiao, JingJing Lu, Gigin Lin, Le Lu

PDNet learns comprehensive and representative deep image features for our tasks and produces more accurate results on both lesion segmentation and RECIST diameter prediction.

Lesion Segmentation

Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss

no code implementations3 May 2021 YouBao Tang, Jinzheng Cai, Ke Yan, Lingyun Huang, Guotong Xie, Jing Xiao, JingJing Lu, Gigin Lin, Le Lu

Accurately segmenting a variety of clinically significant lesions from whole body computed tomography (CT) scans is a critical task on precision oncology imaging, denoted as universal lesion segmentation (ULS).

Computed Tomography (CT) Lesion Segmentation +1

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

no code implementations9 Mar 2021 Jieneng Chen, Ke Yan, Yu-Dong Zhang, YouBao Tang, Xun Xu, Shuwen Sun, Qiuping Liu, Lingyun Huang, Jing Xiao, Alan L. Yuille, Ya zhang, Le Lu

(2) The sampled deep vertex features with positional embedding are mapped into a sequential space and decoded by a multilayer perceptron (MLP) for semantic classification.

Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies

1 code implementation CVPR 2021 Jinzheng Cai, YouBao Tang, Ke Yan, Adam P. Harrison, Jing Xiao, Gigin Lin, Le Lu

In this work, we present deep lesion tracker (DLT), a deep learning approach that uses both appearance- and anatomical-based signals.

14 3D Object Tracking

Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT

1 code implementation5 Sep 2020 Ke Yan, Jinzheng Cai, Youjing Zheng, Adam P. Harrison, Dakai Jin, YouBao Tang, Yuxing Tang, Lingyun Huang, Jing Xiao, Le Lu

For example, DeepLesion is such a large-scale CT image dataset with lesions of various types, but it also has many unlabeled lesions (missing annotations).

Lesion Detection Transfer Learning

One Click Lesion RECIST Measurement and Segmentation on CT Scans

no code implementations21 Jul 2020 Youbao Tang, Ke Yan, Jing Xiao, Ranold M. Summers

Based on the results of the first network, the second one refines the lesion segmentation and RECIST estimation.

Lesion Segmentation

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

no code implementations19 Jul 2020 Youbao Tang, Yu-Xing Tang, Yingying Zhu, Jing Xiao, Ronald M. Summers

We introduce an edge prediction module in E$^2$Net and design an edge distance map between liver and tumor boundaries, which is used as an extra supervision signal to train the edge enhanced network.

Liver Segmentation Tumor Segmentation

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

2 code implementations19 Apr 2019 Youbao Tang, Yu-Xing Tang, Jing Xiao, Ronald M. Summers

To reduce the manual annotation burden and to train a robust lung segmentor that can be adapted to pathological lungs with hazy lung boundaries, an image-to-image translation module is employed to synthesize radiorealistic abnormal CXRs from the source of normal ones for data augmentation.

Data Augmentation Image-to-Image Translation +1

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

1 code implementation18 Jan 2019 Youbao Tang, Ke Yan, Yu-Xing Tang, Jiamin Liu, Jing Xiao, Ronald M. Summers

To address this problem, this work constructs a pseudo mask for each lesion region that can be considered as a surrogate of the real mask, based on which the Mask R-CNN is employed for lesion detection.

Computed Tomography (CT) Lesion Detection

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

no code implementations18 Jul 2018 Youbao Tang, Jinzheng Cai, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers

The first GAN reduces the noise in the CT image and the second GAN generates a higher resolution image with enhanced boundaries and high contrast.

Computed Tomography (CT) Image Enhancement +2

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

no code implementations25 Jun 2018 Youbao Tang, Adam P. Harrison, Mohammadhadi Bagheri, Jing Xiao, Ronald M. Summers

Response evaluation criteria in solid tumors (RECIST) is the standard measurement for tumor extent to evaluate treatment responses in cancer patients.

Multi-Task Learning

Deeply-Supervised Recurrent Convolutional Neural Network for Saliency Detection

no code implementations18 Aug 2016 Youbao Tang, Xiangqian Wu, Wei Bu

This paper proposes a novel saliency detection method by developing a deeply-supervised recurrent convolutional neural network (DSRCNN), which performs a full image-to-image saliency prediction.

Saliency Prediction

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

no code implementations18 Aug 2016 Youbao Tang, Xiangqian Wu

This paper proposes a novel saliency detection method by combining region-level saliency estimation and pixel-level saliency prediction with CNNs (denoted as CRPSD).

Saliency Prediction

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