A Lightweight Network for Accurate Coronary Artery Segmentation Using X-Ray Angiograms
出版年份 2022 全文链接
标题
A Lightweight Network for Accurate Coronary Artery Segmentation Using X-Ray Angiograms
作者
关键词
-
出版物
Frontiers in Public Health
Volume 10, Issue -, Pages -
出版商
Frontiers Media SA
发表日期
2022-05-25
DOI
10.3389/fpubh.2022.892418
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Attention-inception-based U-Net for retinal vessel segmentation with advanced residual
- (2022) Huadeng Wang et al. COMPUTERS & ELECTRICAL ENGINEERING
- CNL-UNet: A novel lightweight deep learning architecture for multimodal biomedical image segmentation with false output suppression
- (2021) Md. Badiuzzaman Shuvo et al. Biomedical Signal Processing and Control
- CCAFFMNet: Dual-spectral semantic segmentation network with channel-coordinate attention feature fusion module
- (2021) Shi Yi et al. NEUROCOMPUTING
- Edge-aware U-net with gated convolution for retinal vessel segmentation
- (2021) Yu Zhang et al. Biomedical Signal Processing and Control
- Main Coronary Vessel Segmentation Using Deep Learning in Smart Medical
- (2020) Zhanchao Xian et al. MATHEMATICAL PROBLEMS IN ENGINEERING
- Coronary angiography image segmentation based on PSPNet
- (2020) Xiliang Zhu et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- VSSC Net: Vessel Specific Skip chain Convolutional Network for blood vessel segmentation
- (2020) Pearl Mary Samuel et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Automatic Segmentation of Coronary Arteries in X-ray Angiograms using Multiscale Analysis and Artificial Neural Networks
- (2019) Fernando Cervantes-Sanchez et al. Applied Sciences-Basel
- Segmentation of vessels in angiograms using convolutional neural networks
- (2018) E. Nasr-Esfahani et al. Biomedical Signal Processing and Control
- Blood vessel segmentation algorithms — Review of methods, datasets and evaluation metrics
- (2018) Sara Moccia et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Joint Segment-level and Pixel-wise Losses for Deep Learning based Retinal Vessel Segmentation
- (2018) Zengqiang Yan et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Multichannel Fully Convolutional Network for Coronary Artery Segmentation in X-Ray Angiograms
- (2018) Jingfan Fan et al. IEEE Access
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- (2017) Vijay Badrinarayanan et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Fully Convolutional Networks for Semantic Segmentation
- (2017) Evan Shelhamer et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Holistically-Nested Edge Detection
- (2017) Saining Xie et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Automatic segmentation of coronary arteries using Gabor filters and thresholding based on multiobjective optimization
- (2016) Ivan Cruz-Aceves et al. Biomedical Signal Processing and Control
- A robust coronary artery identification and centerline extraction method in angiographies
- (2015) Zhixun Li et al. Biomedical Signal Processing and Control
- Correction: Retinal Vessel Segmentation: An Efficient Graph Cut Approach with Retinex and Local Phase
- (2015) Yitian Zhao et al. PLoS One
- Retinal vessels segmentation based on level set and region growing
- (2014) Yu Qian Zhao et al. PATTERN RECOGNITION
- Filtering Airborne Lidar Data by Modified White Top-Hat Transform with Directional Edge Constraints
- (2014) Yong Li et al. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
- Blood vessel segmentation methodologies in retinal images – A survey
- (2012) M.M. Fraz et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Morphological image fusion using the extracted image regions and details based on multi-scale top-hat transform and toggle contrast operator
- (2012) Xiangzhi Bai DIGITAL SIGNAL PROCESSING
- Novel Approach for 3-D Reconstruction of Coronary Arteries From Two Uncalibrated Angiographic Images
- (2009) Jian Yang et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
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