Research graph
References from Synthesizing lumbar computed tomography myelography from plain computed tomography images using a cycle-consistent generative adversarial network. Local targets link to admitted publications; unresolved targets remain external evidence.
A review of lumbar spinal stenosis with intermittent neurogenic claudication: disease and diagnosis
10.1093/pm/pnz161 · 2019 · External reference
Diagnosis of lumbar spinal stenosis: an updated systematic review of the accuracy of diagnostic tests
10.1097/brs.0b013e31828935ac · 2013 · External reference
The value of dynamic radiographic myelography in addition to magnetic resonance imaging in detection lumbar spinal canal stenosis: a prospective study
10.1016/j.clineuro.2016.01.031 · 2016 · External reference
Can recumbent magnetic resonance imaging replace myelography or computed tomography myelography for detecting lumbar spinal stenosis?
10.1007/s00590-013-1209-y · 2013 · External reference
Comparison of magnetic resonance imaging and computed tomography-myelography for quantitative evaluation of lumbar intracanalar cross-section
10.3349/ymj.2011.52.1.137 · 2011 · External reference
Radiographic assessment of degenerative lumbar spinal stenosis: is MRI superior to CT?
10.1007/s00586-016-4724-9 · 2017 · External reference
Role of computed tomography and myelography in the diagnosis of central spinal stenosis
10.2106/00004623-198567020-00009 · 1985 · External reference
Unpaired image-to-image translation using cycle-consistent adversarial networks
2017 · External reference
Imaging evaluation of a proposed 3D generative model for MRI to CT translation in the lumbar spine
10.1016/j.spinee.2023.06.399 · 2023 · External reference
Virtual magnetic resonance lumbar spine images generated from computed tomography images using conditional generative adversarial networks
10.1016/j.radi.2021.10.006 · 2022 · External reference
Spine computed tomography to magnetic resonance image synthesis using generative adversarial networks: a preliminary study
10.3340/jkns.2019.0084 · 2020 · External reference
Lumbar spine computed tomography to magnetic resonance imaging synthesis using generative adversarial network: visual Turing test
10.3390/diagnostics12020530 · 2022 · External reference
Generation of synthetic PET/MR fusion images from MR images using a combination of generative adversarial networks and conditional denoising diffusion probabilistic models based on simultaneous 18F-FDG PET/MR image data of pyogenic spondylodiscitis
10.1016/j.spinee.2024.04.007 · 2024 · External reference
Decompose kV projection using neural network for improved motion tracking in paraspinal SBRT
10.1002/mp.15295 · 2021 · External reference
CBAM: convolutional block attention module
2018 · External reference
Spectral normalization for generative adversarial networks
2018 · External reference
Morphological analysis of Kambin’s triangle using 3D CT/MRI fusion imaging of lumbar nerve root created automatically with artificial intelligence
10.1007/s00586-021-06916-y · 2021 · External reference
Image quality assessment: from error visibility to structural similarity
10.1109/tip.2003.819861 · 2004 · External reference
A new grading system of lumbar central canal stenosis on MRI: an easy and reliable method
10.1007/s00256-011-1153-z · 2011 · External reference
The measurement of observer agreement for categorical data
10.2307/2529310 · 1977 · External reference
Guidelines of the minimum sample size requirements for Kappa agreement test
2017 · External reference
Blood cell images segmentation using deep learning semantic segmentation
2018 · External reference
An active learning approach to train a deep learning algorithm for tumor segmentation from brain MR images
10.1186/s13244-023-01487-6 · 2023 · External reference
CT myelography: clinical indications and imaging findings
10.1148/rg.2020190135 · 2020 · External reference
