A large-scale database and a CNN model for attention-based glaucoma detection
Glaucoma is one of the leading causes of irreversible vision loss. Many approaches have
recently been proposed for automatic glaucoma detection based on fundus images …
recently been proposed for automatic glaucoma detection based on fundus images …
Attention based glaucoma detection: A large-scale database and CNN model
Recently, the attention mechanism has been successfully applied in convolutional neural
networks (CNNs), significantly boosting the performance of many computer vision tasks …
networks (CNNs), significantly boosting the performance of many computer vision tasks …
A deep learning model for automatic detection and classification of disc herniation in magnetic resonance images
T Šušteršič, V Ranković, V Milovanović… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Localization of lumbar discs in magnetic resonance imaging (MRI) is a challenging task, due
to a vast range of shape, size, number, and appearance of discs and vertebrae. Based on a …
to a vast range of shape, size, number, and appearance of discs and vertebrae. Based on a …
Visual feature attribution using wasserstein gans
CF Baumgartner, LM Koch… - Proceedings of the …, 2018 - openaccess.thecvf.com
Attributing the pixels of an input image to a certain category is an important and well-studied
problem in computer vision, with applications ranging from weakly supervised localisation to …
problem in computer vision, with applications ranging from weakly supervised localisation to …
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 …
SpineNet: automated classification and evidence visualization in spinal MRIs
The objective of this work is to automatically produce radiological gradings of spinal lumbar
MRIs and also localize the predicted pathologies. We show that this can be achieved via a …
MRIs and also localize the predicted pathologies. We show that this can be achieved via a …
Weakly-supervised simultaneous evidence identification and segmentation for automated glaucoma diagnosis
Evidence identification, optic disc segmentation and automated glaucoma diagnosis are the
most clinically significant tasks for clinicians to assess fundus images. However, delivering …
most clinically significant tasks for clinicians to assess fundus images. However, delivering …
Automated selection of mid-height intervertebral disc slice in traverse lumbar spine MRI using a combination of deep learning feature and machine learning classifier
Abnormalities and defects that can cause lumbar spinal stenosis often occur in the
Intervertebral Disc (IVD) of the patient's lumbar spine. Their automatic detection and …
Intervertebral Disc (IVD) of the patient's lumbar spine. Their automatic detection and …
Automated measurement of anteroposterior diameter and foraminal widths in MRI images for lumbar spinal stenosis diagnosis
Lumbar Spinal Stenosis causes low back pain through pressures exerted on the spinal
nerves. This can be verified by measuring the anteroposterior diameter and foraminal widths …
nerves. This can be verified by measuring the anteroposterior diameter and foraminal widths …
[HTML][HTML] Automatic semantic segmentation and detection of vertebras and intervertebral discs by neural networks
S Guinebert, E Petit, V Bousson, S Bodard… - Computer Methods and …, 2022 - Elsevier
Objective: To realize a tool for automatic segmentation and detection of lumbar disc
degenerative disease and fractures in MRI images using convolutional neural networks …
degenerative disease and fractures in MRI images using convolutional neural networks …