Automated detection of cerebral microbleeds in MR images: A two-stage deep learning approach
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[1] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] E Mark Haacke,et al. Semiautomated detection of cerebral microbleeds in magnetic resonance images. , 2011, Magnetic resonance imaging.
[3] Stephen M Smith,et al. Fast robust automated brain extraction , 2002, Human brain mapping.
[4] Andreas Charidimou,et al. Cerebral microbleeds: detection, mechanisms and clinical challenges , 2011 .
[5] Shuihua Wang,et al. Cerebral Micro-Bleeding Detection Based on Densely Connected Neural Network , 2019, Front. Neurosci..
[6] Jie Liu,et al. Detecting cerebral microbleeds with transfer learning , 2019, Machine Vision and Applications.
[7] Jose George,et al. Using YOLO based deep learning network for real time detection and localization of lung nodules from low dose CT scans , 2018, Medical Imaging.
[8] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Ross B. Girshick,et al. Fast R-CNN , 2015, 1504.08083.
[10] Ali Farhadi,et al. YOLO9000: Better, Faster, Stronger , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Saifeng Liu,et al. Cerebral microbleed detection using Susceptibility Weighted Imaging and deep learning , 2019, NeuroImage.
[12] Tae-Seong Kim,et al. A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification , 2018, Int. J. Medical Informatics.
[13] Ali Farhadi,et al. You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Edwin Valarezo,et al. Simultaneous Detection and Classification of Breast Masses in Digital Mammograms via a Deep Learning YOLO-based CAD System , 2018, Comput. Methods Programs Biomed..
[15] Bin Sheng,et al. Computer-Assisted Decision Support System in Pulmonary Cancer detection and stage classification on CT images , 2018, J. Biomed. Informatics.
[16] Yu-Chung N. Cheng,et al. Susceptibility weighted imaging (SWI) , 2004, Zeitschrift fur medizinische Physik.
[17] Hao Chen,et al. Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks , 2016, IEEE Transactions on Medical Imaging.
[18] M. A. Al-masni,et al. Detection and classification of the breast abnormalities in digital mammograms via regional Convolutional Neural Network , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[19] Yong Fan,et al. A deep learning model integrating FCNNs and CRFs for brain tumor segmentation , 2017, Medical Image Anal..
[20] Hao Chen,et al. VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images , 2017, NeuroImage.
[21] Max A. Viergever,et al. Efficient detection of cerebral microbleeds on 7.0T MR images using the radial symmetry transform , 2012, NeuroImage.
[22] Sujata Chaudhari,et al. Yolo Real Time Object Detection , 2020 .
[23] Andreas Charidimou,et al. Cerebral microbleeds: a guide to detection and clinical relevance in different disease settings , 2013, Neuroradiology.
[24] Susan M. Chang,et al. Computer-aided detection of radiation-induced cerebral microbleeds on susceptibility-weighted MR images☆ , 2013, NeuroImage: Clinical.
[25] Steven Warach,et al. Cerebral Microbleeds : A Field Guide to their Detection and Interpretation , 2012 .
[26] Monique M. B. Breteler,et al. Cerebral Microbleeds : A Field Guide to their Detection and Interpretation , 2012 .
[27] Tian Liu,et al. Intracranial calcifications and hemorrhages: characterization with quantitative susceptibility mapping. , 2013, Radiology.
[28] F. Ciompi,et al. You Only Look on Lymphocytes Once , 2018 .
[29] Anand Viswanathan,et al. Cerebral microbleeds: overview and implications in cognitive impairment , 2014, Alzheimer's Research & Therapy.
[30] Janine M. Lupo,et al. Toward Automatic Detection of Radiation-Induced Cerebral Microbleeds Using a 3D Deep Residual Network , 2018, Journal of Digital Imaging.
[31] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[32] Mun-Taek Choi,et al. Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks , 2018, Comput. Methods Programs Biomed..