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Yide Ma

Showing results (11-20 of 27) with videos related to

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Medical & Biological Engineering & Computing|May 23, 2022
Correction to: Learning multi‑frequency features in convolutional network for mammography classificationYiming Wang, Yunliang Qi, Chunbo Xu, et al.
Entropy (Basel, Switzerland)|December 3, 2020
An Approach for the Generation of an Nth-Order Chaotic System with Hyperbolic SineJizhao Liu, Jun Ma, Jing Lian, et al.
Entropy (Basel, Switzerland)|December 3, 2020
A Novel Delay Linear Coupling Logistics Map Model for Color Image EncryptionShouliang Li, Weikang Ding, Benshun Yin, et al.
IEEE Transactions on Neural Networks and Learning Systems|December 11, 2014
Region-Based Object Recognition by Color Segmentation Using a Simplified PCNNYuli Chen, Yide Ma, Dong Hwan Kim, et al.
Medical & Biological Engineering & Computing|May 13, 2022
Learning multi-frequency features in convolutional network for mammography classificationYiming Wang, Yunliang Qi, Chunbo Xu, et al.
BMC Medical Imaging|August 9, 2015
Local sparsity enhanced compressed sensing magnetic resonance imaging in uniform discrete curvelet domainBingxin Yang, Min Yuan, Yide Ma, et al.
International Journal of Computer Assisted Radiology and Surgery|June 14, 2016
An SPCNN-GVF-based approach for the automatic segmentation of left ventricle in cardiac cine MR imagesYurun Ma, Li Wang, Yide Ma, et al.
Journal of Digital Imaging|March 18, 2015
An Efficient Approach for Automated Mass Segmentation and Classification in MammogramsMin Dong, Xiangyu Lu, Yide Ma, et al.
Computers in Biology and Medicine|September 10, 2021
FS-UNet: Mass segmentation in mammograms using an encoder-decoder architecture with feature strengtheningJiande Pi, Yunliang Qi, Meng Lou, et al.
Medical Physics|June 1, 2021
DCANet: Dual contextual affinity network for mass segmentation in whole mammogramsMeng Lou, Yunliang Qi, Jie Meng, et al.
Pageof 3

Showing results (11-20 of 27) with videos related to

Sort By:
Pageof 3
Medical & Biological Engineering & Computing|May 23, 2022
Correction to: Learning multi‑frequency features in convolutional network for mammography classificationYiming Wang, Yunliang Qi, Chunbo Xu, et al.
Entropy (Basel, Switzerland)|December 3, 2020
An Approach for the Generation of an Nth-Order Chaotic System with Hyperbolic SineJizhao Liu, Jun Ma, Jing Lian, et al.
Entropy (Basel, Switzerland)|December 3, 2020
A Novel Delay Linear Coupling Logistics Map Model for Color Image EncryptionShouliang Li, Weikang Ding, Benshun Yin, et al.
IEEE Transactions on Neural Networks and Learning Systems|December 11, 2014
Region-Based Object Recognition by Color Segmentation Using a Simplified PCNNYuli Chen, Yide Ma, Dong Hwan Kim, et al.
Medical & Biological Engineering & Computing|May 13, 2022
Learning multi-frequency features in convolutional network for mammography classificationYiming Wang, Yunliang Qi, Chunbo Xu, et al.
BMC Medical Imaging|August 9, 2015
Local sparsity enhanced compressed sensing magnetic resonance imaging in uniform discrete curvelet domainBingxin Yang, Min Yuan, Yide Ma, et al.
International Journal of Computer Assisted Radiology and Surgery|June 14, 2016
An SPCNN-GVF-based approach for the automatic segmentation of left ventricle in cardiac cine MR imagesYurun Ma, Li Wang, Yide Ma, et al.
Journal of Digital Imaging|March 18, 2015
An Efficient Approach for Automated Mass Segmentation and Classification in MammogramsMin Dong, Xiangyu Lu, Yide Ma, et al.
Computers in Biology and Medicine|September 10, 2021
FS-UNet: Mass segmentation in mammograms using an encoder-decoder architecture with feature strengtheningJiande Pi, Yunliang Qi, Meng Lou, et al.
Medical Physics|June 1, 2021
DCANet: Dual contextual affinity network for mass segmentation in whole mammogramsMeng Lou, Yunliang Qi, Jie Meng, et al.
Pageof 3