- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1869-4101
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Convolutional neural networks for brain tumour segmentation ; volume:11 ; number:1 ; day:8 ; month:6 ; year:2020 ; pages:1-9 ; date:12.2020
Insights into imaging ; 11, Heft 1 (8.6.2020), 1-9, 12.2020
- Creator
-
Bhandari, Abhishta
Koppen, Jarrad
Agzarian, Marc
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s13244-020-00869-4
- URN
-
urn:nbn:de:101:1-2020081919572957378673
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:52 AM CEST
Data provider
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Associated
- Bhandari, Abhishta
- Koppen, Jarrad
- Agzarian, Marc
- SpringerLink (Online service)
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Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data
Comparison of wavelet transformations to enhance convolutional neural network performance in brain tumor segmentation
Segmentation of MRI Brain Tumor Image using Optimization based Deep Convolutional Neural networks (DCNN)
Fully automated condyle segmentation using 3D convolutional neural networks
Segmentation for mammography classification utilizing deep convolutional neural network
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SEGMENTATION OF ELECTRICAL SUBSTATIONS USING DEEP CONVOLUTIONAL NEURAL NETWORK
Brain tumour segmentation based on an improved U-Net
Deep Convolutional Neural Networks for Brain Tumour Detection and Analysis
Mask region-based convolutional neural network and VGG-16 inspired brain tumor segmentation
Image classification-based brain tumour tissue segmentation
Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data
Comparison of wavelet transformations to enhance convolutional neural network performance in brain tumor segmentation
Segmentation of MRI Brain Tumor Image using Optimization based Deep Convolutional Neural networks (DCNN)
Fully automated condyle segmentation using 3D convolutional neural networks
Segmentation for mammography classification utilizing deep convolutional neural network
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