2021
DOI: 10.1016/j.cmpb.2021.106074
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Deep neural network for automated simultaneous intervertebral disc (IVDs) identification and segmentation of multi-modal MR images

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Cited by 17 publications
(12 citation statements)
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“…The proposed model achieves a recognition accuracy of 94%. The results in the MICCAI IVD 2018 dataset are said to be validated by comparison with other methods [6].…”
Section: Figure 3 Proposed Unet Modelmentioning
confidence: 99%
“…The proposed model achieves a recognition accuracy of 94%. The results in the MICCAI IVD 2018 dataset are said to be validated by comparison with other methods [6].…”
Section: Figure 3 Proposed Unet Modelmentioning
confidence: 99%
“…To our knowledge, however, only a handful of studies have simultaneously segmented lumbar structures and their adjacent structures on MR images simultaneously [ 15 , 16 ]. Prior studies and segmentation have focused mainly on bones [ 17 , 18 ], discs [ 19 ], and nerves [ 20 ]. Regrettably, the segmentation of automatic lumbar structures and their adjacent structures in MR images has not been systematically investigated before, specifically for 3D segmentation of the large blood vessels, as well as the psoas major muscle.…”
Section: Introductionmentioning
confidence: 99%
“…Currently, computer vision is widely applied in various fields, including medicine, to diagnose and analyze diseases based on medical image. The disorders diagnosed using medical images include thyroid cancer [ 1 ] on ultrasound images, back pain [ 2 ] on computed tomography scans, breast cancer [ 3 ] on mammograms, dental and oral diseases [ 4 ] on radiographic images, abnormalities of spinal intervertebral discs [ 5 , 6 ] on magnetic resonance image, and retinal diseases—diabetes mellitus [ 7 , 8 ] and glaucoma [ 9 , 10 ]—on fundus images. Glaucoma is an eye disease that may be the second-largest cause of blindness in the world.…”
Section: Introductionmentioning
confidence: 99%