Search Results for author: You-Bao Tang

Found 10 papers, 1 papers with code

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

no code implementations14 Jul 2020 Yingying Zhu, You-Bao Tang, Yu-Xing Tang, Daniel C. Elton, Sung-Won Lee, Perry J. Pickhardt, Ronald M. Summers

We expect the utility of our framework will extend to other problems beyond segmentation due to the improved quality of the generated images and enhanced ability to preserve small structures.

Image-to-Image Translation Pancreas Segmentation +1

Bone Suppression on Chest Radiographs With Adversarial Learning

no code implementations8 Feb 2020 Jia Liang, Yu-Xing Tang, You-Bao Tang, Jing Xiao, Ronald M. Summers

Dual-energy (DE) chest radiography provides the capability of selectively imaging two clinically relevant materials, namely soft tissues, and osseous structures, to better characterize a wide variety of thoracic pathology and potentially improve diagnosis in posteroanterior (PA) chest radiographs.

Image-to-Image Translation SSIM +1

Weakly Supervised Lesion Co-segmentation on CT Scans

no code implementations24 Jan 2020 Vatsal Agarwal, You-Bao Tang, Jing Xiao, Ronald M. Summers

In this work, we propose a weakly-supervised co-segmentation model that first generates pseudo-masks from the RECIST slices and uses these as training labels for an attention-based convolutional neural network capable of segmenting common lesions from a pair of CT scans.

Lesion Segmentation

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

no code implementations23 Jan 2020 Vatsal Agarwal, You-Bao Tang, Jing Xiao, Ronald M. Summers

Lesion segmentation on computed tomography (CT) scans is an important step for precisely monitoring changes in lesion/tumor growth.

Computed Tomography (CT) Lesion Segmentation

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

13 code implementations12 Aug 2019 Ke Yan, You-Bao Tang, Yifan Peng, Veit Sandfort, Mohammadhadi Bagheri, Zhiyong Lu, Ronald M. Summers

When reading medical images such as a computed tomography (CT) scan, radiologists generally search across the image to find lesions, characterize and measure them, and then describe them in the radiological report.

Computed Tomography (CT) Lesion Detection +2

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

no code implementations5 Mar 2019 Yu-Xing Tang, You-Bao Tang, Mei Han, Jing Xiao, Ronald M. Summers

Given a chest X-ray image in the testing phase, if it is normal, the learned architecture can well model and reconstruct the content; if it is abnormal, since the content is unseen in the training phase, the model would perform poorly in its reconstruction.

One-class classifier

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

no code implementations25 Jan 2018 Jinzheng Cai, You-Bao Tang, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers

Toward this end, we introduce a convolutional neural network based weakly supervised self-paced segmentation (WSSS) method to 1) generate the initial lesion segmentation on the axial RECIST-slice; 2) learn the data distribution on RECIST-slices; 3) adapt to segment the whole volume slice by slice to finally obtain a volumetric segmentation.

Lesion Segmentation Super-Resolution

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