MATEC Web Conf.
Volume 277, 20192018 International Joint Conference on Metallurgical and Materials Engineering (JCMME 2018)
|Number of page(s)||8|
|Section||Data and Signal Processing|
|Published online||02 April 2019|
- Fleg L, Stone W and Fayad A 2012 Detection of high-risk atherosclerotic plaque:report of the NHLBI Working Group on current status and future directions. JACC Cardiovasc Imaging 5(9) 941-955. [CrossRef] [Google Scholar]
- Ambrose A and Srikanth S 2010 Vulnerable plaques and patients:improving prediction of future coronary events. Am J Med 123(1) 10-16. [CrossRef] [Google Scholar]
- Takashi K, Takashi A and Junya S 2013 OCT compared with IVUS in a coronary lesion assessment: The OPUSCLASS Study. JACC Cardiovascular Imaging 6(10)1095-1104. [CrossRef] [Google Scholar]
- Wang S, Luo J and Ling H 2013 Computer-aided diagnosis data platform by using medical imaging. Chin. J. Biomed. Eng 32(1) 105. [Google Scholar]
- Valgimigli M, Agostoni P and Serruvs PW 2007 Acute coronary syndromes: an emphasis shift from treatment to prevention; and the enduring challenge of vulnerable plaque detection in the cardiac catheterization laboratory. Cardiovasic Med (Hagerstown) 8(4) 221-229. [CrossRef] [Google Scholar]
- Chen X 2014 Research on the Application of Sparse Representation Theory in Medical Image Processing and Analysis (Wuhan: Huazhong University of Science and Technology Press) p 4-10. [Google Scholar]
- Keras Documentation/Image Preprocessing. https://keras.io/preprocessing/image/. last accessed 2018/08/14. [Google Scholar]
- Ronneberger O, Fischer P and Brox T 2015 Int. Conf. on Medical image Computing and Computer-Assisted Intervention (Munich) pp.234-241. [Google Scholar]
- Li X, Chen H, Qi X, Dou Q, Fu C and Heng P 2018 H-DenseUNet: hybrid densely connected UNet for liver and tumor segmentation from CT volumes. IEEE Trans Med Imaging PP(99): 1-1. [CrossRef] [Google Scholar]
- Dong H, Yang G, Liu F, Mo Y and Guo Y 2017 Automatic brain tumor detection and segmentation using U-Net based fully convolutional networks. Conf. on Medical Image Understanding and Analysis. [Google Scholar]
- Girshick R 2015 Fast R-CNN. IEEE Int. Conf. on Computer Vision. [Google Scholar]
- Ren S, He K, Girshick R and Sun J 2015 Faster R-CNN: towards real-time object detection with region proposal networks. Conf. on Neural Information Processing Systems (Montreal) p 91-99. [Google Scholar]
- He K, Zhang X, Ren S and Sun J 2015 Deep residual learning for image recognition. arXiv:1512.03385. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.