Deep-learning approach with convolutional neural network for classification of maximum intensity projections of dynamic contrast-enhanced breast magnetic …

T Fujioka, Y Yashima, J Oyama, M Mori… - Magnetic Resonance …, 2021 - Elsevier
Purpose We aimed to evaluate deep learning approach with convolutional neural networks
(CNNs) to discriminate between benign and malignant lesions on maximum intensity …
被引用次数：41 相关文章

Deep-learning approach with convolutional neural network for classification of maximum intensity projections of dynamic contrast-enhanced breast magnetic …

T Fujioka, Y Yashima, J Oyama… - Magnetic …, 2021 - pubmed.ncbi.nlm.nih.gov
Purpose We aimed to evaluate deep learning approach with convolutional neural networks
(CNNs) to discriminate between benign and malignant lesions on maximum intensity …

Deep-learning approach with convolutional neural network for classification of maximum intensity projections of dynamic contrast-enhanced breast magnetic …

T Fujioka, Y Yashima, J Oyama, M Mori… - Magnetic Resonance …, 2020 - europepmc.org
Purpose We aimed to evaluate deep learning approach with convolutional neural networks
(CNNs) to discriminate between benign and malignant lesions on maximum intensity …

[引用][C] Deep-learning approach with convolutional neural network for classification of maximum intensity projections of dynamic contrast-enhanced breast magnetic …

T Fujioka, Y Yashima, J Oyama, M Mori… - Magnetic Resonance …, 2021 - cir.nii.ac.jp
Deep-learning approach with convolutional neural network for classification of maximum
intensity projections of dynamic contrast-enhanced breast magnetic resonance imaging | CiNii …