[HTML][HTML] Medical image super-resolution for smart healthcare applications: A comprehensive survey

S Umirzakova, S Ahmad, LU Khan, T Whangbo - Information Fusion, 2024‏ - Elsevier
The digital transformation in healthcare, propelled by the integration of deep learning
models and the Internet of Things (IoT), is creating unprecedented opportunities for …

A survey on multimodal data-driven smart healthcare systems: approaches and applications

Q Cai, H Wang, Z Li, X Liu - IEEE Access, 2019‏ - ieeexplore.ieee.org
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 …

Localization and edge-based segmentation of lumbar spine vertebrae to identify the deformities using deep learning models

M Mushtaq, MU Akram, NS Alghamdi, J Fatima… - Sensors, 2022‏ - mdpi.com
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 …

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 …

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 …

Current development and prospects of deep learning in spine image analysis: a literature review

B Qu, J Cao, C Qian, J Wu, J Lin… - … Imaging in Medicine …, 2022‏ - pmc.ncbi.nlm.nih.gov
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 …

An approach to the diagnosis of lumbar disc herniation using deep learning models

AA Prisilla, YL Guo, YK Jan, CY Lin, FY Lin… - … in Bioengineering and …, 2023‏ - frontiersin.org
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 …

[HTML][HTML] Lumbar spine discs classification based on deep convolutional neural networks using axial view MRI

W Mbarki, M Bouchouicha, S Frizzi, F Tshibasu… - Interdisciplinary …, 2020‏ - Elsevier
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 …

Lumbar disease classification using an Involutional neural based VGG Nets (INVGG).

BM Abuhayi, YA Bezabh, AM Ayalew - IEEE Access, 2024‏ - ieeexplore.ieee.org
Degenerative diseases of the lumbar spine, such as spondylolisthesis, disc degeneration,
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

RF Masood, IA Taj, MB Khan, MA Qureshi… - … Signal Processing and …, 2022‏ - Elsevier
Assessment of medical images and diagnostic decision making of lumbar associated
diseases by clinicians is invariably subjective, time consuming and challenging task …