Search Results for author: Baiying Lei

Found 28 papers, 3 papers with code

Brain Structure-Function Fusing Representation Learning using Adversarial Decomposed-VAE for Analyzing MCI

no code implementations23 May 2023 Qiankun Zuo, Baiying Lei, Ning Zhong, Yi Pan, Shuqiang Wang

Integrating the brain structural and functional connectivity features is of great significance in both exploring brain science and analyzing cognitive impairment clinically.

Representation Learning

Brain Diffuser: An End-to-End Brain Image to Brain Network Pipeline

no code implementations11 Mar 2023 Xuhang Chen, Baiying Lei, Chi-Man Pun, Shuqiang Wang

Brain network analysis is essential for diagnosing and intervention for Alzheimer's disease (AD).

ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images

no code implementations16 Feb 2022 Huihui Fang, Fei Li, Huazhu Fu, Xu sun, Xingxing Cao, Fengbin Lin, Jaemin Son, Sunho Kim, Gwenole Quellec, Sarah Matta, Sharath M Shankaranarayana, Yi-Ting Chen, Chuen-heng Wang, Nisarg A. Shah, Chia-Yen Lee, Chih-Chung Hsu, Hai Xie, Baiying Lei, Ujjwal Baid, Shubham Innani, Kang Dang, Wenxiu Shi, Ravi Kamble, Nitin Singhal, Ching-Wei Wang, Shih-Chang Lo, José Ignacio Orlando, Hrvoje Bogunović, Xiulan Zhang, Yanwu Xu, iChallenge-AMD study group

The ADAM challenge consisted of four tasks which cover the main aspects of detecting and characterizing AMD from fundus images, including detection of AMD, detection and segmentation of optic disc, localization of fovea, and detection and segmentation of lesions.

Morphological feature visualization of Alzheimer's disease via Multidirectional Perception GAN

no code implementations25 Nov 2021 Wen Yu, Baiying Lei, Yanyan Shen, Shuqiang Wang, Yong liu, Zhiguang Feng, Yong Hu, Michael K. Ng

In this work, a novel Multidirectional Perception Generative Adversarial Network (MP-GAN) is proposed to visualize the morphological features indicating the severity of AD for patients of different stages.

Generative Adversarial Network

A Prior Guided Adversarial Representation Learning and Hypergraph Perceptual Network for Predicting Abnormal Connections of Alzheimer's Disease

no code implementations12 Oct 2021 Qiankun Zuo, Baiying Lei, Shuqiang Wang, Yong liu, BingChuan Wang, Yanyan Shen

The proposed model can evaluate characteristics of abnormal brain connections at different stages of Alzheimer's disease, which is helpful for cognitive disease study and early treatment.

Representation Learning

3D Brain Reconstruction by Hierarchical Shape-Perception Network from a Single Incomplete Image

no code implementations23 Jul 2021 Bowen Hu, Baiying Lei, Shuqiang Wang, Yong liu, BingChuan Wang, Min Gan, Yanyan Shen

A branching predictor and several hierarchical attention pipelines are constructed to generate point clouds that accurately describe the incomplete images and then complete these point clouds with high quality.

3D Shape Reconstruction

Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysis

no code implementations21 Jul 2021 Junren Pan, Baiying Lei, Yanyan Shen, Yong liu, Zhiguang Feng, Shuqiang Wang

Using multimodal neuroimaging data to characterize brain network is currently an advanced technique for Alzheimer's disease(AD) Analysis.

White Matter Fiber Tractography

Multimodal Representations Learning and Adversarial Hypergraph Fusion for Early Alzheimer's Disease Prediction

no code implementations21 Jul 2021 Qiankun Zuo, Baiying Lei, Yanyan Shen, Yong liu, Zhiguang Feng, Shuqiang Wang

Then two hypergraphs are constructed from the latent representations and the adversarial network based on graph convolution is employed to narrow the distribution difference of hyperedge features.

Alzheimer's Disease Detection Disease Prediction +1

A Point Cloud Generative Model via Tree-Structured Graph Convolutions for 3D Brain Shape Reconstruction

no code implementations21 Jul 2021 Bowen Hu, Baiying Lei, Yanyan Shen, Yong liu, Shuqiang Wang

Fusing medical images and the corresponding 3D shape representation can provide complementary information and microstructure details to improve the operational performance and accuracy in brain surgery.

3D Shape Representation Generative Adversarial Network

Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation

1 code implementation7 Jul 2021 Mohammad Hamghalam, Alejandro F. Frangi, Baiying Lei, Amber L. Simpson

In large studies involving multi protocol Magnetic Resonance Imaging (MRI), it can occur to miss one or more sub-modalities for a given patient owing to poor quality (e. g. imaging artifacts), failed acquisitions, or hallway interrupted imaging examinations.

Brain Tumor Segmentation Segmentation +1

A New Weighting Scheme for Fan-beam and Circle Cone-beam CT Reconstructions

no code implementations6 Jan 2021 Wei Wang, Xiang-Gen Xia, Chuanjiang He, Zemin Ren, Jian Lu, Tianfu Wang, Baiying Lei

In this paper, we first present an arc based algorithm for fan-beam computed tomography (CT) reconstruction via applying Katsevich's helical CT formula to 2D fan-beam CT reconstruction.

Computed Tomography (CT) SSIM

Fine Perceptive GANs for Brain MR Image Super-Resolution in Wavelet Domain

no code implementations9 Nov 2020 Senrong You, Yong liu, Baiying Lei, Shuqiang Wang

Specifically, FP-GANs firstly divides an MR image into low-frequency global approximation and high-frequency anatomical texture in wavelet domain.

Generative Adversarial Network Image Super-Resolution

Convolutional 3D to 2D Patch Conversion for Pixel-wise Glioma Segmentation in MRI Scans

no code implementations20 Oct 2020 Mohammad Hamghalam, Baiying Lei, Tianfu Wang

Structural magnetic resonance imaging (MRI) has been widely utilized for analysis and diagnosis of brain diseases.


Brain Stroke Lesion Segmentation Using Consistent Perception Generative Adversarial Network

no code implementations30 Aug 2020 Shuqiang Wang, Zhuo Chen, Wen Yu, Baiying Lei

The assistant network and the discriminator are employed to jointly decide whether the segmentation results are real or fake.

Generative Adversarial Network Lesion Segmentation +1

A model-guided deep network for limited-angle computed tomography

1 code implementation10 Aug 2020 Wei Wang, Xiang-Gen Xia, Chuanjiang He, Zemin Ren, Jian Lu, Tianfu Wang, Baiying Lei

In this paper, we first propose a variational model for the limited-angle computed tomography (CT) image reconstruction and then convert the model into an end-to-end deep network. We use the penalty method to solve the model and divide it into three iterative subproblems, where the first subproblem completes the sinograms by utilizing the prior information of sinograms in the frequency domain and the second refines the CT images by using the prior information of CT images in the spatial domain, and the last merges the outputs of the first two subproblems.

Computed Tomography (CT) Image Reconstruction

Bidirectional Mapping Generative Adversarial Networks for Brain MR to PET Synthesis

no code implementations8 Aug 2020 Shengye Hu, Baiying Lei, Yong Wang, Zhiguang Feng, Yanyan Shen, Shuqiang Wang

Fusing multi-modality medical images, such as MR and PET, can provide various anatomical or functional information about human body.

Tensorizing GAN with High-Order Pooling for Alzheimer's Disease Assessment

no code implementations3 Aug 2020 Wen Yu, Baiying Lei, Michael K. Ng, Albert C. Cheung, Yanyan Shen, Shuqiang Wang

To the best of our knowledge, the proposed Tensor-train, High-pooling and Semi-supervised learning based GAN (THS-GAN) is the first work to deal with classification on MRI images for AD diagnosis.

Vocal Bursts Intensity Prediction

Do not forget interaction: Predicting fatality of COVID-19 patients using logistic regression

no code implementations30 Jun 2020 Feng Zhou, Tao Chen, Baiying Lei

Amid the ongoing COVID-19 pandemic, whether COVID-19 patients with high risks can be recovered or not depends, to a large extent, on how early they will be treated appropriately before irreversible consequences are caused to the patients by the virus.


High Tissue Contrast MRI Synthesis Using Multi-Stage Attention-GAN for Glioma Segmentation

no code implementations9 Jun 2020 Mohammad Hamghalam, Baiying Lei, Tianfu Wang

We also employ HTC MR images in both the end-to-end and two-stage segmentation structure to confirm the effectiveness of these images.

Generative Adversarial Network Image-to-Image Translation +1

Constrained Multi-shape Evolution for Overlapping Cytoplasm Segmentation

no code implementations8 Apr 2020 Youyi Song, Lei Zhu, Baiying Lei, Bin Sheng, Qi Dou, Jing Qin, Kup-Sze Choi

In the shape evolution, we compensate intensity deficiency for the segmentation by introducing not only the modeled local shape priors but also global shape priors (clump--level) modeled by considering mutual shape constraints of cytoplasms in the clump.

CNN in CT Image Segmentation: Beyound Loss Function for Expoliting Ground Truth Images

no code implementations8 Apr 2020 Youyi Song, Zhen Yu, Teng Zhou, Jeremy Yuen-Chun Teoh, Baiying Lei, Kup-Sze Choi, Jing Qin

Our insight is that feature maps of two CNNs trained respectively on GT and CT images should be similar on some metric space, because they both are used to describe the same objects for the same purpose.

Image Segmentation Semantic Segmentation

A deep network for sinogram and CT image reconstruction

1 code implementation20 Jan 2020 Wei Wang, Xiang-Gen Xia, Chuanjiang He, Zemin Ren, Jian Lu, Tianfu Wang, Baiying Lei

A CT image can be well reconstructed when the sampling rate of the sinogram satisfies the Nyquist criteria and the sampled signal is noise-free.

Denoising Image Reconstruction +1

SANet:Superpixel Attention Network for Skin Lesion Attributes Detection

no code implementations20 Oct 2019 Xinzi He, Baiying Lei, Tianfu Wang

We introduce a superpixel average pooling to reformulate the superpixel classification problem as a superpixel segmentation problem and a SAMis utilized to focus on discriminative superpixel regions and feature channels.

Attribute General Classification +2

Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans

no code implementations27 Sep 2019 Mohammad Hamghalam, Baiying Lei, Tianfu Wang

A comparison of these synthetic images and real images of brain tumor tissue in MR scans showed significant segmentation improvement and decreased the number of real channels for segmentation.

Brain Tumor Segmentation Generative Adversarial Network +2

Fine-Grained Facial Expression Analysis Using Dimensional Emotion Model

no code implementations2 May 2018 Feng Zhou, Shu Kong, Charless Fowlkes, Tao Chen, Baiying Lei

Specifically, we first mapped facial expressions into dimensional measures so that we transformed facial expression analysis from a classification problem to a regression one.

General Classification regression

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