标题
Deep learning with convolutional neural network in radiology
作者
关键词
Deep learning, Convolutional neural network, CT, MRI, PET
出版物
JAPANESE JOURNAL OF RADIOLOGY
Volume 36, Issue 4, Pages 257-272
出版商
Springer Nature
发表日期
2018-03-01
DOI
10.1007/s11604-018-0726-3
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Disease Staging and Prognosis in Smokers Using Deep Learning in Chest Computed Tomography
- (2018) Germán González et al. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
- Transfer learning on fused multiparametric MR images for classifying histopathological subtypes of rhabdomyosarcoma
- (2018) Imon Banerjee et al. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
- Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs
- (2018) David B. Larson et al. RADIOLOGY
- Deep Learning with Convolutional Neural Network for Differentiation of Liver Masses at Dynamic Contrast-enhanced CT: A Preliminary Study
- (2018) Koichiro Yasaka et al. RADIOLOGY
- Liver Fibrosis: Deep Convolutional Neural Network for Staging by Using Gadoxetic Acid–enhanced Hepatobiliary Phase MR Images
- (2018) Koichiro Yasaka et al. RADIOLOGY
- Deep Learning MR Imaging–based Attenuation Correction for PET/MR Imaging
- (2018) Fang Liu et al. RADIOLOGY
- An Automatic Detection System of Lung Nodule Based on Multigroup Patch-Based Deep Learning Network
- (2018) Hongyang Jiang et al. IEEE Journal of Biomedical and Health Informatics
- Quantitative computed tomography texture analysis for estimating histological subtypes of thymic epithelial tumors
- (2017) Koichiro Yasaka et al. EUROPEAN JOURNAL OF RADIOLOGY
- Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network
- (2017) Hu Chen et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Training and Validating a Deep Convolutional Neural Network for Computer-Aided Detection and Classification of Abnormalities on Frontal Chest Radiographs
- (2017) Mark Cicero et al. INVESTIGATIVE RADIOLOGY
- Deep Learning in Mammography
- (2017) Anton S. Becker et al. INVESTIGATIVE RADIOLOGY
- Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status
- (2017) Panagiotis Korfiatis et al. JOURNAL OF DIGITAL IMAGING
- Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network
- (2017) Jianning Chi et al. JOURNAL OF DIGITAL IMAGING
- Deep neural network-based computer-assisted detection of cerebral aneurysms in MR angiography
- (2017) Takahiro Nakao et al. JOURNAL OF MAGNETIC RESONANCE IMAGING
- Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI
- (2017) Andrew P. Leynes et al. JOURNAL OF NUCLEAR MEDICINE
- Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks
- (2017) Kuo Men et al. MEDICAL PHYSICS
- Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks
- (2017) Bulat Ibragimov et al. MEDICAL PHYSICS
- A deep learning method for classifying mammographic breast density categories
- (2017) Aly A. Mohamed et al. MEDICAL PHYSICS
- Precision of quantitative computed tomography texture analysis using image filtering
- (2017) Koichiro Yasaka et al. MEDICINE
- Automated Critical Test Findings Identification and Online Notification System Using Artificial Intelligence in Imaging
- (2017) Luciano M. Prevedello et al. RADIOLOGY
- When Machines Think: Radiology’s Next Frontier
- (2017) Keith J. Dreyer et al. RADIOLOGY
- From Images to Actions: Opportunities for Artificial Intelligence in Radiology
- (2017) Charles E. Kahn RADIOLOGY
- Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks
- (2017) Paras Lakhani et al. RADIOLOGY
- aLow-dose CT via convolutional neural network
- (2017) Hu Chen et al. Biomedical Optics Express
- Pulmonary nodule classification with deep residual networks
- (2017) Aiden Nibali et al. International Journal of Computer Assisted Radiology and Surgery
- Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images
- (2017) QingZeng Song et al. Journal of Healthcare Engineering
- Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin
- (2017) Mohsen Ghafoorian et al. NeuroImage-Clinical
- A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme
- (2017) Jiangwei Lao et al. Scientific Reports
- Impact of hepatocellular carcinoma heterogeneity on computed tomography as a prognostic indicator
- (2017) Shigeru Kiryu et al. Scientific Reports
- Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning
- (2017) Xinggang Wang et al. Scientific Reports
- CT Textural Analysis of Large Primary Renal Cell Carcinomas: Pretreatment Tumor Heterogeneity Correlates With Histologic Findings and Clinical Outcomes
- (2016) Meghan G. Lubner et al. AMERICAN JOURNAL OF ROENTGENOLOGY
- High-resolution CT with new model-based iterative reconstruction with resolution preference algorithm in evaluations of lung nodules: Comparison with conventional model-based iterative reconstruction and adaptive statistical iterative reconstruction
- (2016) Koichiro Yasaka et al. EUROPEAN JOURNAL OF RADIOLOGY
- Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
- (2016) Marios Anthimopoulos et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models
- (2016) Philipp Kickingereder et al. RADIOLOGY
- MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays
- (2016) Hui Li et al. RADIOLOGY
- Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non—Small Cell Lung Cancer
- (2016) Yanqi Huang et al. RADIOLOGY
- Radiomics: Images Are More than Pictures, They Are Data
- (2016) Robert J. Gillies et al. RADIOLOGY
- Measuring Computed Tomography Scanner Variability of Radiomics Features
- (2015) Dennis Mackin et al. INVESTIGATIVE RADIOLOGY
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Primary Esophageal Cancer: Heterogeneity as Potential Prognostic Biomarker in Patients Treated with Definitive Chemotherapy and Radiation Therapy
- (2013) Connie Yip et al. RADIOLOGY
- Model-based iterative reconstruction for reduction of radiation dose in abdominopelvic CT: comparison to adaptive statistical iterative reconstruction
- (2013) Koichiro Yasaka et al. SpringerPlus
- Abdominal CT With Model-Based Iterative Reconstruction (MBIR): Initial Results of a Prospective Trial Comparing Ultralow-Dose With Standard-Dose Imaging
- (2012) Perry J. Pickhardt et al. AMERICAN JOURNAL OF ROENTGENOLOGY
- Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique
- (2012) Masaki Katsura et al. EUROPEAN RADIOLOGY
- Model-Based Iterative Reconstruction Technique for Ultralow-Dose Computed Tomography of the Lung
- (2012) Yoshitake Yamada et al. INVESTIGATIVE RADIOLOGY
- Measurements of heterogeneity in gliomas on computed tomography relationship to tumour grade
- (2012) Karoline Skogen et al. JOURNAL OF NEURO-ONCOLOGY
- Rhabdomyosarcoma: Review of the Children's Oncology Group (COG) soft-tissue Sarcoma committee experience and rationale for current COG studies
- (2012) Suman Malempati et al. PEDIATRIC BLOOD & CANCER
- Filtered Back Projection, Adaptive Statistical Iterative Reconstruction, and a Model-based Iterative Reconstruction in Abdominal CT: An Experimental Clinical Study
- (2012) Zsuzsanna Deák et al. RADIOLOGY
- Assessment of Primary Colorectal Cancer Heterogeneity by Using Whole-Tumor Texture Analysis: Contrast-enhanced CT Texture as a Biomarker of 5-year Survival
- (2012) Francesca Ng et al. RADIOLOGY
- Assessment of Response to Tyrosine Kinase Inhibitors in Metastatic Renal Cell Cancer: CT Texture as a Predictive Biomarker
- (2011) Vicky Goh et al. RADIOLOGY
- IDH1andIDH2Mutations in Gliomas
- (2009) Hai Yan et al. NEW ENGLAND JOURNAL OF MEDICINE
- An Integrated Genomic Analysis of Human Glioblastoma Multiforme
- (2008) D. W. Parsons et al. SCIENCE
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search