Deep Neural Network-Based Semantic Segmentation of Microvascular Decompression Images

[1]  Mark Fisher,et al.  Retinal vessel segmentation using multi-scale textons derived from keypoints , 2015, Comput. Medical Imaging Graph..

[2]  Yun Tian,et al.  An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures , 2016, Comput. Math. Methods Medicine.

[3]  Joseph F. Murray,et al.  Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation , 2010, Neural Computation.

[4]  Gabriela Csurka,et al.  An Efficient Approach to Semantic Segmentation , 2011, International Journal of Computer Vision.

[5]  Ronald M. Summers,et al.  DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation , 2015, MICCAI.

[6]  François Chollet,et al.  Xception: Deep Learning with Depthwise Separable Convolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Ke Chen,et al.  Automated Vessel Segmentation Using Infinite Perimeter Active Contour Model with Hybrid Region Information with Application to Retinal Images , 2015, IEEE Transactions on Medical Imaging.

[8]  Paul Y. S. Cheung,et al.  Vessel Extraction Under Non-Uniform Illumination: A Level Set Approach , 2008, IEEE Transactions on Biomedical Engineering.

[9]  Carlos Fernandez-Lozano,et al.  Automatic multiscale vascular image segmentation algorithm for coronary angiography , 2018, Biomed. Signal Process. Control..

[10]  Nils Daniel Forkert,et al.  Vascular Segmentation in TOF MRA Images of the Brain Using a Deep Convolutional Neural Network , 2017, CVII-STENT/LABELS@MICCAI.

[11]  Zengchang Qin,et al.  Automated coronary artery tree segmentation in X-ray angiography using improved Hessian based enhancement and statistical region merging. , 2018, Computer methods and programs in biomedicine.

[12]  Zhen Chen,et al.  Morphological Multiscale Enhancement, Fuzzy Filter and Watershed for Vascular Tree Extraction in Angiogram , 2011, Journal of Medical Systems.

[13]  Ronald M. Summers,et al.  A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations , 2014, MICCAI.

[14]  András Hajdu,et al.  Segmentation of retinal vessels by means of directional response vector similarity and region growing , 2015, Comput. Biol. Medicine.

[15]  Saeed Sadri,et al.  Segmentation of Coronary Vessels by Combining the Detection of Centerlines and Active Contour Model , 2011, 2011 7th Iranian Conference on Machine Vision and Image Processing.

[16]  Mohammad H. Jafari,et al.  Vessel extraction in X-ray angiograms using deep learning , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[17]  Shin Ishii,et al.  Deep learning of fMRI big data: a novel approach to subject-transfer decoding , 2015, ArXiv.

[18]  Yu Liu,et al.  A review of semantic segmentation using deep neural networks , 2017, International Journal of Multimedia Information Retrieval.

[19]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Tuan-Tu Huynh,et al.  A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification , 2020, International journal of molecular sciences.

[21]  John D. Kelleher,et al.  A U-Net Deep Learning Framework for High Performance Vessel Segmentation in Patients With Cerebrovascular Disease , 2019, Front. Neurosci..

[22]  Jian Sun,et al.  Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Xinbo Gao,et al.  Lightweight Image Super-Resolution with Information Multi-distillation Network , 2019, ACM Multimedia.

[24]  Trevor Darrell,et al.  Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[26]  Roberto Cipolla,et al.  SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[28]  S Nirmala Devi,et al.  Comparison of active contour models for image segmentation in X-ray coronary angiogram images , 2008, Journal of medical engineering & technology.

[29]  Sang Jun Park,et al.  Scale-space approximated convolutional neural networks for retinal vessel segmentation , 2019, Comput. Methods Programs Biomed..

[30]  George Papandreou,et al.  Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation , 2018, ECCV.

[31]  A. Osareh,et al.  Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering , 2014, Journal of medical signals and sensors.

[32]  Xiaoyi Jiang,et al.  A self-adaptive matched filter for retinal blood vessel detection , 2014, Machine Vision and Applications.

[33]  Rajeev Srivastava,et al.  Retinal blood vessels segmentation by using Gumbel probability distribution function based matched filter , 2016, Comput. Methods Programs Biomed..

[34]  Vince D. Calhoun,et al.  Deep learning for neuroimaging: a validation study , 2013, Front. Neurosci..

[35]  Taein Lee Active contour models , 2005 .

[36]  David Menotti,et al.  A Semi-Automatic Method for Segmentation of the Coronary Artery Tree from Angiography , 2009, 2009 XXII Brazilian Symposium on Computer Graphics and Image Processing.

[37]  Yi Wang,et al.  Retinal blood vessel segmentation using fully convolutional network with transfer learning , 2018, Comput. Medical Imaging Graph..

[38]  Xinbo Gao,et al.  Fast and Accurate Single Image Super-Resolution via Information Distillation Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[39]  Trang T. Le,et al.  Using deep neural networks and biological subwords to detect protein S-sulfenylation sites , 2020, Briefings Bioinform..

[40]  Su-Lin Lee,et al.  Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis , 2017, Lecture Notes in Computer Science.

[41]  Keshab K. Parhi,et al.  Iterative Vessel Segmentation of Fundus Images , 2015, IEEE Transactions on Biomedical Engineering.

[42]  Elli Angelopoulou,et al.  Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database , 2013, IET Image Process..

[43]  Yizhou Yu,et al.  FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation , 2019, ArXiv.

[44]  Jun Fu,et al.  Dual Attention Network for Scene Segmentation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[45]  J.J. Bellanger,et al.  A Level Set Method for Vessel Segmentation in Coronary Angiography , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[46]  Kotagiri Ramamohanarao,et al.  An effective retinal blood vessel segmentation method using multi-scale line detection , 2013, Pattern Recognit..

[47]  Xiaogang Wang,et al.  Medical image classification with convolutional neural network , 2014, 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV).

[48]  Lei Zhang,et al.  Multi-level deep supervised networks for retinal vessel segmentation , 2017, International Journal of Computer Assisted Radiology and Surgery.

[49]  Xiaogang Wang,et al.  Pyramid Scene Parsing Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[50]  Jie Liu,et al.  Residual Feature Distillation Network for Lightweight Image Super-Resolution , 2020, ECCV Workshops.

[51]  Tariq Mahmood Khan,et al.  A Multi-Scale Directional Line Detector for Retinal Vessel Segmentation , 2019, Sensors.

[52]  Vivienne Sze,et al.  Efficient Processing of Deep Neural Networks: A Tutorial and Survey , 2017, Proceedings of the IEEE.

[53]  Yongtian Wang,et al.  Saliency driven vasculature segmentation with infinite perimeter active contour model , 2017, Neurocomputing.

[54]  Alejandro F. Frangi,et al.  Muliscale Vessel Enhancement Filtering , 1998, MICCAI.

[55]  Beizhan Wang,et al.  3D vasculature segmentation using localized hybrid level-set method , 2014, BioMedical Engineering OnLine.

[56]  Iasonas Kokkinos,et al.  DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[57]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[58]  Iasonas Kokkinos,et al.  Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs , 2014, ICLR.

[59]  V. Goh,et al.  Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks , 2015, PloS one.

[60]  George Papandreou,et al.  Rethinking Atrous Convolution for Semantic Image Segmentation , 2017, ArXiv.

[61]  Wang Yongtian,et al.  Automatic segmentation of coronary angiograms based on fuzzy inferring and probabilistic tracking , 2010, Biomedical engineering online.