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README.md
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- n<1K
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---
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cite:
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@misc{yang2023segmentation,
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title={Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network},
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author={Xiaoyu Yang and Lijian Xu and Simon Yu and Qing Xia and Hongsheng Li and Shaoting Zhang},
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year={2023},
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eprint={2305.04208},
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archivePrefix={arXiv}
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primaryClass={id='eess.IV' full_name='Image and Video Processing' is_active=True alt_name=None in_archive='eess' is_general=False description='Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.'}
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}
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# Coronary Artery Dataset (CCA)
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This dataset collects many cases of CTA images with coronary artery disease named the CCA dataset.
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cite:
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```bibtex
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@misc{yang2023segmentation,
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title={Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network},
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author={Xiaoyu Yang and Lijian Xu and Simon Yu and Qing Xia and Hongsheng Li and Shaoting Zhang},
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year={2023},
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eprint={2305.04208},
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archivePrefix={arXiv}
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}
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```
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