Search Results for author: Yingying Zhu

Found 13 papers, 4 papers with code

Automated Generation of Accurate \& Fluent Medical X-ray Reports

1 code implementation27 Aug 2021 Hoang T. N. Nguyen, Dong Nie, Taivanbat Badamdorj, Yujie Liu, Yingying Zhu, Jason Truong, Li Cheng

Our paper focuses on automating the generation of medical reports from chest X-ray image inputs, a critical yet time-consuming task for radiologists.

Cross-view Geo-localization with Evolving Transformer

no code implementations2 Jul 2021 Hongji Yang, Xiufan Lu, Yingying Zhu

In this work, we address the problem of cross-view geo-localization, which estimates the geospatial location of a street view image by matching it with a database of geo-tagged aerial images.

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

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

COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature

1 code implementation11 Jun 2020 Yifan Peng, Yu-Xing Tang, Sung-Won Lee, Yingying Zhu, Ronald M. Summers, Zhiyong Lu

(1) We show that COVID-19-CT-CXR, when used as additional training data, is able to contribute to improved DL performance for the classification of COVID-19 and non-COVID-19 CT. (2) We collected CT images of influenza and trained a DL baseline to distinguish a diagnosis of COVID-19, influenza, or normal or other types of diseases on CT. (3) We trained an unsupervised one-class classifier from non-COVID-19 CXR and performed anomaly detection to detect COVID-19 CXR.

Anomaly Detection Computed Tomography (CT) +1

Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Detection

no code implementations22 May 2020 Yingying Zhu, Daniel C. Elton, SungWon Lee, Perry J. Pickhardt, Ronald M. Summers

In medical imaging applications, preserving small structures is important since these structures can carry information which is highly relevant for disease diagnosis.

Image Reconstruction Object Detection +1

GeoCapsNet: Aerial to Ground view Image Geo-localization using Capsule Network

no code implementations12 Apr 2019 Bin Sun, Chen Chen, Yingying Zhu, Jianmin Jiang

The task of cross-view image geo-localization aims to determine the geo-location (GPS coordinates) of a query ground-view image by matching it with the GPS-tagged aerial (satellite) images in a reference dataset.

Image Retrieval

Attention-based Pyramid Aggregation Network for Visual Place Recognition

no code implementations1 Aug 2018 Yingying Zhu, Jiong Wang, Lingxi Xie, Liang Zheng

Visual place recognition is challenging in the urban environment and is usually viewed as a large scale image retrieval task.

Image Retrieval Visual Place Recognition

A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome

1 code implementation13 Mar 2018 Yingying Zhu, Mert R. Sabuncu

An additional layer of complexity is that, in real life, the amount and type of data available for each patient can differ significantly.

Bayesian Inference

Complex Non-Rigid Motion 3D Reconstruction by Union of Subspaces

no code implementations CVPR 2014 Yingying Zhu, Dong Huang, Fernando de la Torre, Simon Lucey

The task of estimating complex non-rigid 3D motion through a monocular camera is of increasing interest to the wider scientific community.

3D Reconstruction Structure from Motion

Context-Aware Modeling and Recognition of Activities in Video

no code implementations CVPR 2013 Yingying Zhu, Nandita M. Nayak, Amit K. Roy-Chowdhury

This is motivated from the observations that the activities related in space and time rarely occur independently and can serve as the context for each other.

Motion Segmentation

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