4.7 Article

Semi-Supervised Dual Stream Segmentation Network for Fundus Lesion Segmentation

Related references

Note: Only part of the references are listed.
Article Radiology, Nuclear Medicine & Medical Imaging

Automated segmentation of retinal nonperfusion area in fluorescein angiography in retinal vein occlusion using convolutional neural networks

Ziqi Tang et al.

Summary: The study developed CNN methods for segmenting RNP in RVO in FA images, achieving excellent results in agreement with physicians. CNN performance was significantly improved by using the adaptive histogram-based data augmentation method. Training CNNs with averaged labels from multiple physicians resulted in the best consensus with all physicians.

MEDICAL PHYSICS (2021)

Article Biochemical Research Methods

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

Fabian Isensee et al.

Summary: nnU-Net is a deep learning-based image segmentation method that automatically configures itself for diverse biological and medical image segmentation tasks, offering state-of-the-art performance as an out-of-the-box tool.

NATURE METHODS (2021)

Article Biochemical Research Methods

In vivo fluorescence molecular imaging of the vascular endothelial growth factor in rats with early diabetic retinopathy

Lu Zhang et al.

Summary: This study utilized fluorescence molecular imaging technology and a VEGF-targeted fluorescence imaging probe to detect and predict the response to anti-VEGF treatment, further understanding the role of VEGF in diabetic retinopathy. It has the potential to enhance early detection of DR disease and provide insights into the understanding of anti-VEGF treatment.

BIOMEDICAL OPTICS EXPRESS (2021)

Article Neurosciences

MF-Net: Multi-Scale Information Fusion Network for CNV Segmentation in Retinal OCT Images

Qingquan Meng et al.

Summary: CNV segmentation is crucial for ophthalmologists, but remains challenging due to various factors. A novel multi-scale information fusion network is proposed, which outperforms other state-of-the-art algorithms for CNV segmentation.

FRONTIERS IN NEUROSCIENCE (2021)

Article Neurosciences

DW-Net: Dynamic Multi-Hierarchical Weighting Segmentation Network for Joint Segmentation of Retina Layers With Choroid Neovascularization

Lianyu Wang et al.

Summary: In this paper, a novel dynamic multi-hierarchical weighting segmentation network (DW-Net) is proposed for simultaneous segmentation of retinal layers and CNV. Experimental results show that DW-Net achieves better performance than other state-of-the-art methods.

FRONTIERS IN NEUROSCIENCE (2021)

Article Computer Science, Artificial Intelligence

BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation

Changqian Yu et al.

Summary: Separating low-level details and high-level semantics is key to achieving high accuracy and efficiency in real-time semantic segmentation. The proposed architecture, called Bilateral Segmentation Network (BiSeNet V2), effectively handles feature representations through detail and semantics branches, striking a balance between speed and accuracy to outperform existing methods.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2021)

Proceedings Paper Computer Science, Artificial Intelligence

Dual Encoder Fusion U-Net (DEFU-Net) for Cross-manufacturer Chest X-ray Segmentation

Lipei Zhang et al.

Summary: Many methods based on deep learning have been applied to medical image segmentation, with the dual encoder fusion U-Net framework, DEFU-Net, achieving better performance in Chest X-ray dataset by capturing global and local spatial information and preserving contextual and spatial details.

2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) (2021)

Proceedings Paper Engineering, Biomedical

A Generative Adversarial Framework for Capillary Non-perfusion Regions Segmentation in Fundus Fluorescein Angiograms

Mulin Cai et al.

Summary: This paper proposes a novel generative adversarial framework for the segmentation of non-perfusion regions in fundus fluorescein angiography images, achieving more accurate results than state-of-the-art approaches. The method is validated on 138 clinical images, demonstrating its effectiveness in clinical judgment and treatment selection for diabetic retinal vascular diseases.

MEDICAL IMAGING 2021: IMAGE PROCESSING (2021)

Article Biochemical Research Methods

D-UNet: A Dimension-Fusion U Shape Network for Chronic Stroke Lesion Segmentation

Yongjin Zhou et al.

Summary: The paper proposes a new medical image segmentation method called D-UNet, which combines 2D and 3D convolutions to achieve better segmentation performance with shorter computation time than 3D networks. Additionally, an Enhance Mixing Loss function is introduced to address the issue of data imbalance between positive and negative samples for network training.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2021)

Article Computer Science, Artificial Intelligence

CGNet: A Light-Weight Context Guided Network for Semantic Segmentation

Tianyi Wu et al.

Summary: The research presents a lightweight and efficient semantic segmentation network CGNet, which captures contextual information in all stages of the network through context-guided technology, designed specifically to increase segmentation accuracy and reduce memory usage. Experimental results show that CGNet achieves good performance on the Cityscapes dataset.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2021)

Article Computer Science, Artificial Intelligence

Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation

Tanya Nair et al.

MEDICAL IMAGE ANALYSIS (2020)

Article Computer Science, Artificial Intelligence

Deep co-training for semi-supervised image segmentation

Jizong Peng et al.

PATTERN RECOGNITION (2020)

Article Multidisciplinary Sciences

Appearance of cysts and capillary non perfusion areas in diabetic macular edema using two different OCTA devices

Mariacristina Parravano et al.

SCIENTIFIC REPORTS (2020)

Article Computer Science, Interdisciplinary Applications

Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images

Faisal Mahmood et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)

Article Computer Science, Artificial Intelligence

A fully convolutional two-stream fusion network for interactive image segmentation

Yang Hu et al.

NEURAL NETWORKS (2019)

Article Computer Science, Artificial Intelligence

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Liang-Chieh Chen et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2018)

Article Computer Science, Artificial Intelligence

Automatic Segmentation of Retinal Layer in OCT Images With Choroidal Neovascularization

Dehui Xiang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2018)

Review Public, Environmental & Occupational Health

Global causes of blindness and distance vision impairment 1990-2020: a systematic review and meta-analysis

Seth R. Flaxman et al.

LANCET GLOBAL HEALTH (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Densely Connected Convolutional Networks

Gao Huang et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)