标题
Variability and reproducibility in deep learning for medical image segmentation
作者
关键词
-
出版物
Scientific Reports
Volume 10, Issue 1, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2020-08-13
DOI
10.1038/s41598-020-69920-0
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。- Demystifying Parallel and Distributed Deep Learning
- (2019) Tal Ben-Nun et al. ACM COMPUTING SURVEYS
- An overview of deep learning in medical imaging focusing on MRI
- (2018) Alexander Selvikvåg Lundervold et al. Zeitschrift fur Medizinische Physik
- Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
- (2017) Konstantinos Kamnitsas et al. MEDICAL IMAGE ANALYSIS
- Brain tumor segmentation with Deep Neural Networks
- (2017) Mohammad Havaei et al. MEDICAL IMAGE ANALYSIS
- A survey on deep learning in medical image analysis
- (2017) Geert Litjens et al. MEDICAL IMAGE ANALYSIS
- Automatic Segmentation of Kidneys using Deep Learning for Total Kidney Volume Quantification in Autosomal Dominant Polycystic Kidney Disease
- (2017) Kanishka Sharma et al. Scientific Reports
- Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities
- (2017) Mohsen Ghafoorian et al. Scientific Reports
- Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR
- (2017) Stefano Trebeschi et al. Scientific Reports
- Multiscale CNNs for Brain Tumor Segmentation and Diagnosis
- (2016) Liya Zhao et al. Computational and Mathematical Methods in Medicine
- Deep Learning Guided Partitioned Shape Model for Anterior Visual Pathway Segmentation
- (2016) Awais Mansoor et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images
- (2016) Sergio Pereira et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation
- (2016) Tom Brosch et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Automatic Segmentation of MR Brain Images With a Convolutional Neural Network
- (2016) Pim Moeskops et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Fast and robust segmentation of the striatum using deep convolutional neural networks
- (2016) Hongyoon Choi et al. JOURNAL OF NEUROSCIENCE METHODS
- 1,500 scientists lift the lid on reproducibility
- (2016) Monya Baker NATURE
- Deep MRI brain extraction: A 3D convolutional neural network for skull stripping
- (2016) Jens Kleesiek et al. NEUROIMAGE
- A semi-automatic computer-aided method for surgical template design
- (2016) Xiaojun Chen et al. Scientific Reports
- The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
- (2015) Bjoern H. Menze et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Deep convolutional neural networks for multi-modality isointense infant brain image segmentation
- (2015) Wenlu Zhang et al. NEUROIMAGE
- Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool
- (2015) Abdel Aziz Taha et al. BMC MEDICAL IMAGING
- Tissue segmentation of head and neck CT images for treatment planning: A multiatlas approach combined with intensity modeling
- (2013) Valerio Fortunati et al. MEDICAL PHYSICS
- Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging
- (2013) Aviv Mezer et al. NATURE MEDICINE
- Comparison of Segmentation Methods for Melanoma Diagnosis in Dermoscopy Images
- (2009) Margarida Silveira et al. IEEE Journal of Selected Topics in Signal Processing
- Brain Anatomical Structure Segmentation by Hybrid Discriminative/Generative Models
- (2008) Zhuowen Tu et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started