Convolutional neural network for discriminating nasopharyngeal carcinoma and benign hyperplasia on MRI

[1] Werbos PJ(1990)Backpropagation through time: what it does and how to do it Proc IEEE 78 1550-1560

[2] Soniya PS(2015)A review on advances in deep learning IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions 2015 1-6

[3] Singh L(2017)Deep learning vs. conventional machine learning: pilot study of WMH segmentation in brain MRI with absence or mild vascular pathology J Imaging 3 66-41

[4] Rachmadi M(2019)Deep learning versus conventional machine learning for detection of healthcare-associated infections in French clinical narratives Methods Inf Med 58 31-685

[5] Valdés-Hernández M(2018)Deep learning and medical diagnosis: a review of literature Multimodal Technol Interact 2 47-248

[6] Agan M(2018)A review of denoising medical images using machine learning approaches Curr Med Imaging Rev 14 675-1441

[7] Komura T(2019)Overview of image-to-image translation by use of deep neural networks: denoising, super-resolution, modality conversion, and reconstruction in medical imaging Radiol Phys Technol 12 235-340

[8] Rabhi S(2020)Deep learning–based MR-to-CT synthesis: the influence of varying gradient echo–based MR images as input channels Magn Reson Med 83 1429-1995

[9] Jakubowicz J(2018)Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI J Magn Reson Imaging 48 330-7

[10] Metzger M-H(2018)Deep residual learning for accelerated MRI using magnitude and phase networks IEEE Trans Biomed Eng 65 1985-954

[1] Werbos PJ(1990)Backpropagation through time: what it does and how to do it Proc IEEE 78 1550-1560

[2] Soniya PS(2015)A review on advances in deep learning IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions 2015 1-6

[3] Singh L(2017)Deep learning vs. conventional machine learning: pilot study of WMH segmentation in brain MRI with absence or mild vascular pathology J Imaging 3 66-41

[4] Rachmadi M(2019)Deep learning versus conventional machine learning for detection of healthcare-associated infections in French clinical narratives Methods Inf Med 58 31-685

[5] Valdés-Hernández M(2018)Deep learning and medical diagnosis: a review of literature Multimodal Technol Interact 2 47-248

[6] Agan M(2018)A review of denoising medical images using machine learning approaches Curr Med Imaging Rev 14 675-1441

[7] Komura T(2019)Overview of image-to-image translation by use of deep neural networks: denoising, super-resolution, modality conversion, and reconstruction in medical imaging Radiol Phys Technol 12 235-340

[8] Rabhi S(2020)Deep learning–based MR-to-CT synthesis: the influence of varying gradient echo–based MR images as input channels Magn Reson Med 83 1429-1995

[9] Jakubowicz J(2018)Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI J Magn Reson Imaging 48 330-7

[10] Metzger M-H(2018)Deep residual learning for accelerated MRI using magnitude and phase networks IEEE Trans Biomed Eng 65 1985-954