Medical Image Analysis

Transcription

1 Medical Image Analysis 1 Co-trained convolutional neural networks for automated detection of prostate cancer in multiparametric MRI, 2017, Medical Image Analysis 2 Graph-based prostate extraction in t2-weighted images for prostate cancer detection. In: Fuzzy Systems and Knowledge Discovery (FSKD), th International Conference on. IEEE, pp Prostate cancer localization with multispectral mri using cost-sensitive support vector machines and conditional random fields. IEEE Trans. Image Process. 19 (9), Region-specific hierarchical segmentation of mr prostate using discriminative learning. MICCAI Grand Challenge: Prostate MR Image Segmentation, Detection of prostate cancer by integration of line-scan diffu- sion, t2-mapping and t2-weighted magnetic resonance imaging; a multichannel statistical classifier. Med. Phys. 30 (9), Elastic registration of multimodal prostate mri and histology via multiattribute combined mutual information. Med. Phys. 38 (4), Automatic classification of prostate can- cer gleason scores from multiparametric magnetic resonance images. Proc. Natl. Acad. Sci. 112 (46), E6265 E Prostate cancer detection with multi-parametric mri: logistic regression analysis of quantitative t2, diffusion-weighted imaging, and dynamic contrast-enhanced mri. J. Magn. Reson. Imaging 30 (2), Computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric mri: a review. Comput. Biol. Med. 60, Automated comput- er-aided detection of prostate cancer in mr images: from a whole-organ to a zone-based approach. In: SPIE Medical Imaging. International Society for Optics and Photonics, p G Comput- er-aided detection of prostate cancer in mri. IEEE Trans. Med. Imaging 33 (5), A prostate cancer computer-aided diagnosis system using mul- timodal magnetic resonance imaging and targeted biopsy labels. In: SPIE medi- cal imaging. International Society for Optics and Photonics, p G Comput- er-aided diagnosis of prostate cancer in the peripheral zone using multiparametric mri. Phys. Med. Biol. 57 (12), Decision support system for localizing prostate cancer based on multiparametric magnetic resonance imaging. Med. Phys. 39 (7), Deep convolutional neural networks for computer-aided de- tection: Cnn architectures, dataset characteristics and transfer learning. IEEE Trans. Med. Imaging 35 (5), Convolutional neural networks for medical image analysis: full training or fine tuning? IEEE Trans. Med. Imaging 35 (5), Multi-kernel graph embedding for detection, gleason grading of prostate cancer via mri/mrs. Med. Image Anal. 17 (2), Computer aided-di- agnosis of prostate cancer on multiparametric mri: a technical review of current research. BioMed Res. Int Automated Detection of Clinically Significant Prostate Cancer in mp-mri Images based on an End-to-End Deep Neural Network, IEEE Transactions on Medical Imaging, Automated Diagnosis of Prostate Cancer in Multi-Parametric MRI based on Multimodal Convolutional Neural Networks, Physics in Medicine and Biology, A skeletal Similarity Metric for Quality Evalu8ation of Retinal Vessel Segmentation, IEEE Transactions on Medical Imaging, Joint Segment-level and Pixel level Losses for Deep Learning based Retinal Vessel Segmentation, IEEE Transactions on Biomedical Engineering, Accurate Face Alignment and Adaptive Patch Selection for Heart Rate Estimation from Videos under Realistic Scenarios, Plos One, Automatic Artery-Vein Separation from Thoracic CT Images Using Integer Programming. 2015

2 MICCAI 25 Automated integer programming based separation of arteries and veins from thoracic CT images. 2016, Medical Image Analysis 26 Automatic Pulmonary Artery-Vein Separation and Classification in Computed Tomography Using Tree Partitioning and Peripheral Vessel Matching. 2016, IEEE Transactions on Medical Imaging Simultaneous Localization and Mapping & Visual Odometry 27 Probabilistic Data Association for Semantic SLAM, ICRA, SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networks, ICRA, Visibility Enhancement for Underwater Visual SLAM based on Underwater Light Scattering Model, ICRA, Multi-UAV Collaborative Monocular SLAM, ICRA, Keyframe-based Dense Planar SLAM, ICRA, RGB-T SLAM: A Flexible SLAM Framework By Combining Appearance and Thermal Information, ICRA, Real-time Monocular Dense Mapping on Aerial Robots Using Visual-Inertial Fusion, ICRA, MonoRGBD-SLAM: Simultaneous Localization and Mapping Using Both Monocular and RGBD Cameras, ICRA, Real-time Local 3D Reconstruction for Aerial Inspection using Superpixel Expansion, ICRA, PL-SLAM: Real-Time Monocular Visual SLAM with Points and Lines, ICRA, RFM-SLAM: Exploiting Relative Feature, ICRA, Measurements to Separate Orientation and Position Estimationin SLAM, ICRA, Illumination Change Robustness in Direct Visual SLAM, ICRA, Monocular Visual Odometry: Sparse Joint Optimisation or Dense Alternation, ICRA, RRD-SLAM: Radial-distorted Rolling-shutter Direct SLAM, ICRA, Application-oriented Design Space Exploration for SLAM Algorithms, ICRA, Convergence and Consistency Analysis for A 3D Invariant-EKFSLAM, ICRA, Robust Visual Localization in Changing Lighting Conditions ICRA, Direct Monocular Odometry Using Points and Lines ICRA, Accurate Stereo Visual Odometry with Gamma Distributions ICRA, Semi-Dense Visual Odometry for RGB-D Cameras UsingApproximate Nearest Neighbour Fields ICRA, Direct Visual Odometry in Low Light using Binary Deors ICRA, 2017 Object Detection and Tracking 49 Deep but Lightweight Neural Networks for Real-time Object Detection, arxiv: OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks, ICLR, Rich feature hierarchies for accurate object detection and semantic segmentation, CVPR, Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition, ECCV, Fast R-CNN, arxiv:

3 54 Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, arxiv: R-CNN minus R, arxiv: End-to-end people detection in crowded scenes, arxiv: Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks 58 You Only Look Once: Unified, Real-Time Object Detection, arxiv: Deep Residual Learning for Image Recognition 60 Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning 61 R-FCN: Object Detection via Region-based Fully Convolutional Networks 62 SSD: Single Shot MultiBox Detector, arxiv: Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network, arxiv: DeepTrack: Learning Discriminative Feature Representations by Convolutional Neural Networks for Visual Tracking, BMVC, Learning a Deep Compact Image Representation for Visual Tracking, NIPS, Hierarchical Convolutional Features for Visual Tracking, 67 Visual Tracking with fully Convolutional Networks, ICCV Learning Multi-Domain Convolutional Neural Networks for Visual Tracking 69 Delving Deeper into Convolutional Networks for Learning Video Representations 70 Deep Multi Scale Video Prediction Beyond Mean Square Error", ICLR Other Vision Tops 71 Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation, ECCV, Efficient piecewise training of deep structured models for semantic segmentation, arxiv: Semantic Image Segmentation via Deep Parsing Network, arxiv: / ICCV Feedforward Semantic Segmentation With Zoom-Out Features, CVPR, Joint Calibration for Semantic Segmentation, arxiv: Deep Hierarchical Parsing for Semantic Segmentation, CVPR, 77 Pusing the Boundaries of Boundary Detection Using deep Learning", ICLR 2016, 78 Weakly supervised graph based semantic segmentation by learning communities of image-parts", ICCV, FlowNet: Learning Optical Flow with Convolutional Networks, arxiv: Learning a Deep Convolutional Network for Image Super-Resolution, ECCV, Accurate Image Super-Resolution Using Very Deep Convolutional Networks, arxiv: , 82 Deeply-Recursive Convolutional Network for Image Super-Resolution, arxiv: , 83 Perceptual Losses for Real-Time Style Transfer and Super-Resolution, arxiv: , Long-term Recurrent Convolutional Networks for Visual Recognition and Description, CVPR, 85 Learning to Generate Chairs with Convolutional Neural Networks", CVPR, 86 "DRAW: A Recurrent Neural Network For Image Generation", ICML,

4 87 Generative Adversarial Networks, NIPS, Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks, NIPS, 89 Variationally Auto-Encoded Deep Gaussian Processes", ICLR "Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks", ICLR 2016, 91 Finding Action Tubes, CVPR, 92 DeepFace: Closing the Gap to Human-Level Performance in Face Verification, CVPR, DeepID3: Face Recognition with Very Deep Neural Networks, 94 Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue,ECCV Depth Map Prediction from a Single Image using a Multi-Scale Deep Network, NIPS, Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields, IEEE Transactions on Pattern Analysis and Machine Intelligence, Deep3d: Fully automatic 2d-to-3d video conversion with deep convolutional neural networks. arxiv preprint arxiv: (2016) 98 Holistically-Nested Edge Detection, arxiv: DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection, CVPR, 100 Is object localization for free? Weakly-supervised learning with convolutional neural networks, CVPR, 101 Deep Filter Banks for Texture Recognition and Segmentation, CVPR, 102 Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields, CVPR, Deepcut: Joint subset partition and labeling for multi person pose estimation, CVPR, Convolutional pose machines, CVPR, Stacked hourglass networks for human pose estimation, ECCV, Flowing convnets for human pose estimation in videos, ICCV, 107 Joint training of a convolutional network and a graphical model for human pose estimation, NIPS, Understanding image representations by measuring their equivariance and equivalence, CVPR, 109 Deep Neural Networks are Easily Fooled:High Confidence Predictions for Unrecognizable Images, CVPR,

5 1: 1,2,3 2: 22,25,26 3: 33,34,35 4: 47,49,50 5: 53,55,56 6: 3,4,7 7: 5,6,7 8: 33,35,36 9: 63,66,67 10: 7,8,9 11: 73,76,77 12: 7,9,11 13: 10,11,12 14: 55,58,59 15: 31,34,35 16: 51,54,55 17: 35,37,38 18: 13,16,17 19: 16,17,18 20: 49,50,51 21: 73,75,76 22: 19,20,21 23: 71,72,73 24: 19,22,23 25: 22, 23, 24 26: 44,45,46 27: 1,2,4 28: 89,90,91 29: 55,57,58 30: 24,25,26 31: 27,28,29 32: 57,59,60 33: 73,74,75 34: 79,82,83 35: 29,31,32 36: 65,68,69 37: 31,32,33 38: 32,33,34 39: 10,13,14 40: 1,2,5 41: 5,6,8 42: 33,36,37 43: 35,36,37 44: 13,15,16 45: 87,89,90 46: 53,56,57 47: 65,67,68 48: 37,40,41 49: 42,43,44 50: 59,61,62 51: 67,70,71 52: 85,86,87 53: 75,78,79 54: 1,2,26 55: 47,48,49 56: 3,4,5 57: 63,65,66 58: 16,18,19 59: 49,51,52 60: 69,72,73 61: 51,52,53 62: 83,86,87 63: 13,14,15 64: 93,95,96 65: 3,4,6 66: 105,108,109 67: 55,56,57 68: 93,94,95 69: 10,12,13 70: 57,58,59 71: 103,106,107 72: 85,88,89 73: 99,101,102 74: 42,44,45 75: 105,106,107 76: 97,98,99 77: 91,94,95 78: 101,104,105 79: 63,64,65 80: 47,50,51 81: 83,85,86 82: 79,81,82 83: 37,39,40 84: 93,96,97 85: 67,68,69 86: 95,97,98 87: 42,45,46 88: 77,79,80 89: 89,92,93 90: 49,52,53 91: 19,21,22 92: 71,73,74 93: 99,102,103 94: 27,30,31 95: 16,19,20 96: 69,71,72

6 97: 75,76,77 98: 101,103,104 99: 101,102, : 89,91,92 101: 69,70,71 102: 97,100, : 79,80,81 104: 65,66,67 105:29,30,31 105: 81,82,83 107: 91,93,94 108: 103,105, : 83,84,85 110: 5,6,9 111:51,53,54 112: 22,24,25 113: 85,87,88 114:57,60,61 115: 87,88,89 116: 71,74,75 117:59,62,63 118: 44,47,48 119: 77,78,79 120:69,71,72 121: 91,92,93 122:81,83,84 123: 61,63,64 124: 1,2,25 125: 53,54,55 126:29,32,33 127: 95,96,97 128:67,69,70 129: 95,98,99 130: 61,62,63 131: 97,99, :77,80,81 133: 99,100, : 59,60,61 135: 35,38,39 136: 44,46,47 137: 75,77,78 138:61,64,65 139: 103,104, : 81,84,85 141:27,29,30 142: 87,90,91 143: 105,107, :37,38,39