Artificial intelligence in spinal imaging: current status and future directions
Y Cui, J Zhu, Z Duan, Z Liao, S Wang… - International journal of …, 2022 - mdpi.com
Spinal maladies are among the most common causes of pain and disability worldwide.
Imaging represents an important diagnostic procedure in spinal care. Imaging investigations …
Imaging represents an important diagnostic procedure in spinal care. Imaging investigations …
Spine-GAN: Semantic segmentation of multiple spinal structures
Spinal clinicians still rely on laborious workloads to conduct comprehensive assessments of
multiple spinal structures in MRIs, in order to detect abnormalities and discover possible …
multiple spinal structures in MRIs, in order to detect abnormalities and discover possible …
3D multi-scale FCN with random modality voxel dropout learning for intervertebral disc localization and segmentation from multi-modality MR images
Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The
localization and segmentation of IVDs are important for spine disease diagnosis and …
localization and segmentation of IVDs are important for spine disease diagnosis and …
Automatic localization and identification of vertebrae in arbitrary field-of-view CT scans
B Glocker, J Feulner, A Criminisi, DR Haynor… - … Image Computing and …, 2012 - Springer
This paper presents a new method for automatic localization and identification of vertebrae
in arbitrary field-of-view CT scans. No assumptions are made about which section of the …
in arbitrary field-of-view CT scans. No assumptions are made about which section of the …
Deep spine: automated lumbar vertebral segmentation, disc-level designation, and spinal stenosis grading using deep learning
The high prevalence of spinal stenosis results in a large volume of MRI imaging, yet
interpretation can be time-consuming with high inter-reader variability even among the most …
interpretation can be time-consuming with high inter-reader variability even among the most …
[KSIĄŻKA][B] Healthcare data analytics
CK Reddy, CC Aggarwal - 2015 - books.google.com
Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …
Analytics provides an understanding of the analytical techniques currently available to solve …
Multi-modal vertebrae recognition using transformed deep convolution network
Y Cai, M Landis, DT Laidley, A Kornecki, A Lum… - … medical imaging and …, 2016 - Elsevier
Automatic vertebra recognition, including the identification of vertebra locations and naming
in multiple image modalities, are highly demanded in spinal clinical diagnoses where large …
in multiple image modalities, are highly demanded in spinal clinical diagnoses where large …
Spine detection in CT and MR using iterated marginal space learning
Examinations of the spinal column with both, Magnetic Resonance (MR) imaging and
Computed Tomography (CT), often require a precise three-dimensional positioning …
Computed Tomography (CT), often require a precise three-dimensional positioning …
Fast automatic vertebrae detection and localization in pathological ct scans-a deep learning approach
Automatic detection and localization of vertebrae in medical images are highly sought after
techniques for computer-aided diagnosis systems of the spine. However, the presence of …
techniques for computer-aided diagnosis systems of the spine. However, the presence of …
Unifying neural learning and symbolic reasoning for spinal medical report generation
Automated medical report generation in spine radiology, ie, given spinal medical images
and directly create radiologist-level diagnosis reports to support clinical decision making, is …
and directly create radiologist-level diagnosis reports to support clinical decision making, is …