[1]
|
Computer-aided breast cancer detection and classification in mammography: A comprehensive review
Computers in Biology and Medicine,
2023
DOI:10.1016/j.compbiomed.2023.106554
|
|
|
[2]
|
Improving the diagnostic performance of computed tomography angiography for intracranial large arterial stenosis by a novel super-resolution algorithm based on multi-scale residual denoising generative adversarial network
Clinical Imaging,
2023
DOI:10.1016/j.clinimag.2023.01.009
|
|
|
[3]
|
Computer-aided breast cancer detection and classification in mammography: A comprehensive review
Computers in Biology and Medicine,
2023
DOI:10.1016/j.compbiomed.2023.106554
|
|
|
[4]
|
Improving the diagnostic performance of computed tomography angiography for intracranial large arterial stenosis by a novel super-resolution algorithm based on multi-scale residual denoising generative adversarial network
Clinical Imaging,
2023
DOI:10.1016/j.clinimag.2023.01.009
|
|
|
[5]
|
Artificial Intelligence in Dentistry
2023
DOI:10.1007/978-3-031-43827-1_18
|
|
|
[6]
|
Computer-aided breast cancer detection and classification in mammography: A comprehensive review
Computers in Biology and Medicine,
2023
DOI:10.1016/j.compbiomed.2023.106554
|
|
|
[7]
|
Breast mass regions classification from mammograms using convolutional neural networks and transfer learning.
Journal of Modern Optics,
2023
DOI:10.1080/09500340.2024.2313724
|
|
|
[8]
|
Computer-aided breast cancer detection and classification in mammography: A comprehensive review
Computers in Biology and Medicine,
2023
DOI:10.1016/j.compbiomed.2023.106554
|
|
|
[9]
|
Diabetic foot ulcers monitoring by employing super resolution and noise reduction deep learning techniques
Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments,
2022
DOI:10.1145/3529190.3529214
|
|
|
[10]
|
Visual and quantitative evaluation of microcalcifications in mammograms with deep learning-based super-resolution
European Journal of Radiology,
2022
DOI:10.1016/j.ejrad.2022.110433
|
|
|
[11]
|
Multi-scale residual denoising GAN model for producing super-resolution CTA images
Journal of Ambient Intelligence and Humanized Computing,
2022
DOI:10.1007/s12652-021-03009-y
|
|
|
[12]
|
Diabetic foot ulcers monitoring by employing super resolution and noise reduction deep learning techniques
The15th International Conference on PErvasive Technologies Related to Assistive Environments,
2022
DOI:10.1145/3529190.3529214
|
|
|
[13]
|
Visual and quantitative evaluation of microcalcifications in mammograms with deep learning-based super-resolution
European Journal of Radiology,
2022
DOI:10.1016/j.ejrad.2022.110433
|
|
|
[14]
|
Image Semantic Recognition Algorithm of Colorimetric Sensor Array Based on Deep Convolutional Neural Network
Advances in Multimedia,
2022
DOI:10.1155/2022/4325117
|
|
|
[15]
|
Underwater Object Detection and Reconstruction Based on Active Single-Pixel Imaging and Super-Resolution Convolutional Neural Network
Sensors,
2021
DOI:10.3390/s21010313
|
|
|
[16]
|
Attenuation correction using deep learning for brain perfusion SPECT images
Annals of Nuclear Medicine,
2021
DOI:10.1007/s12149-021-01600-z
|
|
|
[17]
|
Artificial Intelligence for MR Image Reconstruction: An Overview for Clinicians
Journal of Magnetic Resonance Imaging,
2021
DOI:10.1002/jmri.27078
|
|
|
[18]
|
Introduction to deep learning: minimum essence required to launch a research
Japanese Journal of Radiology,
2020
DOI:10.1007/s11604-020-00998-2
|
|
|
[19]
|
Artificial Intelligence for MR Image Reconstruction: An Overview for Clinicians
Journal of Magnetic Resonance Imaging,
2020
DOI:10.1002/jmri.27078
|
|
|
[20]
|
1. Deep Learning Super-resolution in Medical Imaging: What Is It and How to Use It
Japanese Journal of Radiological Technology,
2020
DOI:10.6009/jjrt.2020_JSRT_76.5.524
|
|
|
[21]
|
Deep learning-based super-resolution images for synchronous measurement of temperature and deformation at elevated temperature
Optik,
2020
DOI:10.1016/j.ijleo.2020.165764
|
|
|
[22]
|
Improvement in Image Quality of CBCT during Treatment by Cycle Generative Adversarial Network
Japanese Journal of Radiological Technology,
2020
DOI:10.6009/jjrt.2020_JSRT_76.11.1173
|
|
|
[23]
|
Deep-Learning-Based Computer-Aided Systems for Breast Cancer Imaging: A Critical Review
Applied Sciences,
2020
DOI:10.3390/app10228298
|
|
|
[24]
|
Overview of image-to-image translation by use of deep neural networks: denoising, super-resolution, modality conversion, and reconstruction in medical imaging
Radiological Physics and Technology,
2019
DOI:10.1007/s12194-019-00520-y
|
|
|
[25]
|
Deep convolutional neural networks for mammography: advances, challenges and applications
BMC Bioinformatics,
2019
DOI:10.1186/s12859-019-2823-4
|
|
|
[26]
|
Computed tomography super-resolution using deep convolutional neural network
Physics in Medicine & Biology,
2018
DOI:10.1088/1361-6560/aacdd4
|
|
|