Search Results for author: Jianlong Yang

Found 10 papers, 4 papers with code

Towards ultra-low-cost smartphone microscopy

no code implementations28 Nov 2023 Haoran Zhang, Weiyi Zhang, Zirui Zuo, Jianlong Yang

The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications.

Image Enhancement

Cross-attention learning enables real-time nonuniform rotational distortion correction in OCT

no code implementations7 Jun 2023 Haoran Zhang, Jianlong Yang, Jingqian Zhang, Shiqing Zhao, Aili Zhang

Nonuniform rotational distortion (NURD) correction is vital for endoscopic optical coherence tomography (OCT) imaging and its functional extensions, such as angiography and elastography.

Annotation-efficient learning for OCT segmentation

1 code implementation6 May 2023 Haoran Zhang, Jianlong Yang, Ce Zheng, Shiqing Zhao, Aili Zhang

Compared to the widely-used U-Net model with 100% training data, our method only requires ~10% of the data for achieving the same segmentation accuracy, and it speeds the training up to ~3. 5 times.

Segmentation

Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images

no code implementations5 Oct 2021 Kang Zhou, Jing Li, Weixin Luo, Zhengxin Li, Jianlong Yang, Huazhu Fu, Jun Cheng, Jiang Liu, Shenghua Gao

To mitigate this problem, in this paper, we propose a novel Proxy-bridged Image Reconstruction Network (ProxyAno) for anomaly detection in medical images.

Anomaly Detection Image Reconstruction

CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging

1 code implementation15 Oct 2020 Lei Mou, Yitian Zhao, Huazhu Fu, Yonghuai Liu, Jun Cheng, Yalin Zheng, Pan Su, Jianlong Yang, Li Chen, Alejandro F Frang, Masahiro Akiba, Jiang Liu

Automated detection of curvilinear structures, e. g., blood vessels or nerve fibres, from medical and biomedical images is a crucial early step in automatic image interpretation associated to the management of many diseases.

Management Segmentation

Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images

1 code implementation ECCV 2020 Kang Zhou, Yuting Xiao, Jianlong Yang, Jun Cheng, Wen Liu, Weixin Luo, Zaiwang Gu, Jiang Liu, Shenghua Gao

In the end, we further utilize the reconstructed image to extract the structure and measure the difference between structure extracted from original and the reconstructed image.

Anatomy Anomaly Detection +2

ROSE: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model

1 code implementation10 Jul 2020 Yuhui Ma, Huaying Hao, Huazhu Fu, Jiong Zhang, Jianlong Yang, Jiang Liu, Yalin Zheng, Yitian Zhao

To address these issues, for the first time in the field of retinal image analysis we construct a dedicated Retinal OCT-A SEgmentation dataset (ROSE), which consists of 229 OCT-A images with vessel annotations at either centerline-level or pixel level.

Retinal Vessel Segmentation Segmentation

Open-Narrow-Synechiae Anterior Chamber Angle Classification in AS-OCT Sequences

no code implementations9 Jun 2020 Huaying Hao, Huazhu Fu, Yanwu Xu, Jianlong Yang, Fei Li, Xiulan Zhang, Jiang Liu, Yitian Zhao

However, clinical diagnosis requires a more discriminating ACA three-class system (i. e., open, narrow, or synechiae angles) for the benefit of clinicians who seek better to understand the progression of the spectrum of angle-closure glaucoma types.

Binary Classification General Classification

Sparse-GAN: Sparsity-constrained Generative Adversarial Network for Anomaly Detection in Retinal OCT Image

no code implementations28 Nov 2019 Kang Zhou, Shenghua Gao, Jun Cheng, Zaiwang Gu, Huazhu Fu, Zhi Tu, Jianlong Yang, Yitian Zhao, Jiang Liu

With the development of convolutional neural network, deep learning has shown its success for retinal disease detection from optical coherence tomography (OCT) images.

Anomaly Detection Generative Adversarial Network

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