- Tytuł :
- Learned iterative segmentation of highly variable anatomy from limited data: Applications to whole heart segmentation for congenital heart disease
- Autorzy :
- Źródło :
- In Medical Image Analysis August 2022 80
-
Czasopismo naukowe
Wyszukujesz frazę ""Brosch, Tom"" wg kryterium: Autor
- Tytuł :
- Model-based segmentation using neural network-based boundary detectors: Application to prostate and heart segmentation in MR images
- Autorzy :
- Źródło :
- In Machine Learning with Applications 15 December 2021 6
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Czasopismo naukowe
- Tytuł :
- Automated detection and segmentation of thoracic lymph nodes from CT using 3D foveal fully convolutional neural networks
- Autorzy :
- Źródło :
- BMC Medical Imaging. 21(1)
-
Czasopismo naukowe
- Tytuł :
- Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controls
- Autorzy :
- Źródło :
- In NeuroImage: Clinical 2018 17:169-178
-
Czasopismo naukowe
- Tytuł :
- Spinal cord grey matter segmentation challenge
- Autorzy :
- Źródło :
- In NeuroImage 15 May 2017 152:312-329
-
Czasopismo naukowe
- Tytuł :
- Organ-At-Risk Segmentation in Brain MRI Using Model-Based Segmentation: Benefits of Deep Learning-Based Boundary Detectors
- Autorzy :
- Źródło :
- Shape in Medical Imaging : International Workshop, ShapeMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. 11167:291-299
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Książka elektroniczna
- Tytuł :
- Deep Learning-Based Boundary Detection for Model-Based Segmentation with Application to MR Prostate Segmentation
- Autorzy :
- Źródło :
- Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 : 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part IV. 11073:515-522
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Książka elektroniczna
- Tytuł :
- Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease
- Autorzy :
- Źródło :
- Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support : 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. 11045:334-342
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Książka elektroniczna
- Tytuł :
- 3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images
- Autorzy :
- Temat :
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Electrical Engineering and Systems Science - Image and Video Processing
Computer Science - Computer Vision and Pattern Recognition - Dostęp URL :
-
https://explore.openaire.eu/search/publication?articleId=arXiv_______::793698c9c526ba4a56e3d5f80eadb65c
http://arxiv.org/abs/2003.07923
- Tytuł :
- Abdomen Segmentation in 3D Fetal Ultrasound Using CNN-powered Deformable Models
- Autorzy :
- Źródło :
- Fetal, Infant and Ophthalmic Medical Image Analysis : International Workshop, FIFI 2017, and 4th International Workshop, OMIA 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings. 10554:52-61
- Materiał oryginalny :
- C. Lorenz—We thank the authors of [9] for providing the automatic landmark detection.
-
Książka elektroniczna
- Tytuł :
- Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections
- Autorzy :
- Źródło :
- Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support : Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings. 10553:330-337
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Książka elektroniczna
- Tytuł :
- Foveal fully convolutional nets for multi-organ segmentation
- Autorzy :
- Temat :
-
Image segmentation
Data domain
Modalities
Artificial intelligence
business.industry
business
Pattern recognition
Deep learning
Foveal
Segmentation
Multi organ
Computer science
Convolutional neural network - Źródło :
- Medical Imaging: Image Processing
- Dostęp URL :
- https://explore.openaire.eu/search/publication?articleId=doi_________::353f9e6bcb0a0eab45957bda894fd687
- Tytuł :
- Deep Learning of Brain Lesion Patterns for Predicting Future Disease Activity in Patients with Early Symptoms of Multiple Sclerosis
- Autorzy :
- Źródło :
- Deep Learning and Data Labeling for Medical Applications : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. 10008:86-94
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Książka elektroniczna
- Tytuł :
- Corpus Callosum Segmentation in Brain MRIs via Robust Target-Localization and Joint Supervised Feature Extraction and Prediction
- Autorzy :
- Źródło :
- Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 : 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II. 9901:406-414
-
Książka elektroniczna
- Tytuł :
- Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation
- Autorzy :
- Źródło :
- Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 : 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III. 9351:3-11
-
Książka elektroniczna
- Tytuł :
- Spinal cord grey matter segmentation challenge
- Autorzy :
- Temat :
-
Balgrist University Hospital, Swiss Spinal Cord Injury Center
610 Medicine & health - Źródło :
-
Prados, Ferran; et al; Dávid, Gergely; Freund, Patrick (2017). Spinal cord grey matter segmentation challenge. NeuroImage, 152:312-329.
Neuroimage, 152, 312-329 - Opis pliku :
- application/pdf
- Dostęp URL :
-
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d47c929c33bbce8ffcceda9e890b47c
https://www.zora.uzh.ch/id/eprint/136397/1/ZORA136397.pdf
- Tytuł :
- Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2D and 3D Images.
- Autorzy :
- Źródło :
- Neural Computation. 2015, Vol. 27 Issue 1, p211-227. 17p. 3 Diagrams, 4 Charts, 2 Graphs.
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Czasopismo naukowe
- Tytuł :
- Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation
- Autorzy :
- Źródło :
- Machine Learning in Medical Imaging : 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014. Proceedings. 8679:117-124
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Książka elektroniczna
- Tytuł :
- Modeling the Variability in Brain Morphology and Lesion Distribution in Multiple Sclerosis by Deep Learning
- Autorzy :
- Źródło :
- Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 : 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II. 8674:462-469
-
Książka elektroniczna
- Tytuł :
- Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation
- Autorzy :
- Temat :
-
Electrical and Electronic Engineering
Computer Science Applications
Radiological and Ultrasound Technology
Software
Scale-space segmentation
Segmentation-based object categorization
Pattern recognition
Artificial neural network
Segmentation
Feature extraction
Computer vision
Artificial intelligence
business.industry
business
Image segmentation
Encoder
Computer science
Feature (computer vision) - Dostęp URL :
- https://explore.openaire.eu/search/publication?articleId=doi_________::95c629507ead142e390fb51656630ea6