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[HTML][HTML] Medical image super-resolution for smart healthcare applications: A comprehensive survey
The digital transformation in healthcare, propelled by the integration of deep learning
models and the Internet of Things (IoT), is creating unprecedented opportunities for …
models and the Internet of Things (IoT), is creating unprecedented opportunities for …
A survey on multimodal data-driven smart healthcare systems: approaches and applications
Multimodal data-driven approach has emerged as an important driving force for smart
healthcare systems with applications ranging from disease analysis to triage, diagnosis and …
healthcare systems with applications ranging from disease analysis to triage, diagnosis and …
Localization and edge-based segmentation of lumbar spine vertebrae to identify the deformities using deep learning models
The lumbar spine plays a very important role in our load transfer and mobility. Vertebrae
localization and segmentation are useful in detecting spinal deformities and fractures …
localization and segmentation are useful in detecting spinal deformities and fractures …
A deep learning model for automatic detection and classification of disc herniation in magnetic resonance images
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 …
Automatic lumbar spinal MRI image segmentation with a multi-scale attention network
H Li, H Luo, W Huan, Z Shi, C Yan, L Wang… - Neural Computing and …, 2021 - Springer
Lumbar spinal stenosis (LSS) is a lumbar disease with a high incidence in recent years.
Accurate segmentation of the vertebral body, lamina and dural sac is a key step in the …
Accurate segmentation of the vertebral body, lamina and dural sac is a key step in the …
Current development and prospects of deep learning in spine image analysis: a literature review
Background and Objective As the spine is pivotal in the support and protection of human
bodies, much attention is given to the understanding of spinal diseases. Quick, accurate …
bodies, much attention is given to the understanding of spinal diseases. Quick, accurate …
An approach to the diagnosis of lumbar disc herniation using deep learning models
Background: In magnetic resonance imaging (MRI), lumbar disc herniation (LDH) detection
is challenging due to the various shapes, sizes, angles, and regions associated with bulges …
is challenging due to the various shapes, sizes, angles, and regions associated with bulges …
[HTML][HTML] Lumbar spine discs classification based on deep convolutional neural networks using axial view MRI
Axial Lumbar disc herniation recognition is a difficult task to achieve, due to many
challenges such as complex background, noise, blurry image. Lumbar discs are small joints …
challenges such as complex background, noise, blurry image. Lumbar discs are small joints …
Lumbar disease classification using an Involutional neural based VGG Nets (INVGG).
Degenerative diseases of the lumbar spine, such as spondylolisthesis, disc degeneration,
and lumbar spinal stenosis, are major contributors to global disability. Accurate classification …
and lumbar spinal stenosis, are major contributors to global disability. Accurate classification …
Deep learning based vertebral body segmentation with extraction of spinal measurements and disorder disease classification
Assessment of medical images and diagnostic decision making of lumbar associated
diseases by clinicians is invariably subjective, time consuming and challenging task …
diseases by clinicians is invariably subjective, time consuming and challenging task …