Automated analysis of spinal MRI using deep learning

Automated analysis of spinal MRI using deep learning

<p>The objective of this thesis is the automation of radiological gradings in spinal lumbar Magnetic Resonance Images (MRIs). Solving this is extremely beneficial as this in a way would help in the standardization of gradings especially for back pain research. The output of the research done i...

Fuld beskrivelse

Bibliografiske detaljer
Hovedforfatter:	Jamaludin, M
Andre forfattere:	Kadir, T
Format:	Thesis
Sprog:	English
Udgivet:	2017

Lignende værker

Automated radiological analysis of spinal MRI
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Automated Segmentation of Brain Tumor MRI Images Using Deep Learning
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Deep learning for the fully automated segmentation of the inner ear on MRI
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Automatic modic changes classification in spinal MRI
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Udgivet: (2016)

Automated Brain Tumor Segmentation and Classification in MRI Using YOLO-Based Deep Learning
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Udgivet: (2024-01-01)

Automated volumetry of meningiomas in contrast-enhanced T1-Weighted MRI using deep learning
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Udgivet: (2024-04-01)

Deep learning model for automated detection and classification of degenerative cord signal abnormality, spinal canal and neural foraminal stenosis on cervical spine MRI
af: J.H.J. Tan, et al.
Udgivet: (2024-01-01)

Spinal disease diagnosis assistant based on MRI images using deep transfer learning methods
af: Junbo Xuan, et al.
Udgivet: (2023-02-01)

Could automated machine-learned MRI grading aid epidemiological studies of lumbar spinal stenosis? Validation within the Wakayama spine study
af: Yuyu Ishimoto, et al.
Udgivet: (2020-03-01)

Deep Learning Model for Classifying Metastatic Epidural Spinal Cord Compression on MRI
af: James Thomas Patrick Decourcy Hallinan, et al.
Udgivet: (2022-05-01)

Automatic multiclass intramedullary spinal cord tumor segmentation on MRI with deep learning
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Udgivet: (2021-01-01)

Deep learning-based automated segmentation of resection cavities on postsurgical epilepsy MRI
af: T. Campbell Arnold, et al.
Udgivet: (2022-01-01)

Automated brain tumor recognition using equilibrium optimizer with deep learning approach on MRI images
af: Mahmoud Ragab, et al.
Udgivet: (2024-11-01)

Trustworthy Deep Learning For The Automated Quantification Of The Fatty Infiltration Of The Rotator Cuff Muscles Using MRI
af: Laith Alzubaidi, et al.
Udgivet: (2024-11-01)

SpineNet: Automated classification and evidence visualization in spinal MRIs
af: Jamaludin, A, et al.
Udgivet: (2017)

A deep learning model for detection of cervical spinal cord compression in MRI scans
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Udgivet: (2021-05-01)

Automated brain tumor diagnostics: Empowering neuro-oncology with deep learning-based MRI image analysis
af: Subathra Gunasekaran, et al.
Udgivet: (2024-01-01)

Automated Detection of Spinal Lesions From CT Scans via Deep Transfer Learning
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Udgivet: (2024-01-01)

Fully Automated Deep Learning-Based Renal Mass Detection on Multi-Parametric MRI
af: Rohini Gaikar, et al.
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Towards fully automated segmentation of rat cardiac MRI by leveraging deep learning frameworks
af: Daniel Fernández-Llaneza, et al.
Udgivet: (2022-06-01)

Automated detection, labelling and radiological grading of clinical spinal MRIs
af: Windsor, R, et al.
Udgivet: (2024)

Automated detection, labelling and radiological grading of clinical spinal MRIs
af: Rhydian Windsor, et al.
Udgivet: (2024-07-01)

Benign and malignant diagnosis of spinal tumors based on deep learning and weighted fusion framework on MRI
af: Hong Liu, et al.
Udgivet: (2022-05-01)

Automated Segmentation of Infarct Lesions in T1-Weighted MRI Scans Using Variational Mode Decomposition and Deep Learning
af: May Phu Paing, et al.
Udgivet: (2021-03-01)

Automated Detection and Measurement of Dural Sack Cross-Sectional Area in Lumbar Spine MRI Using Deep Learning
af: Babak Saravi, et al.
Udgivet: (2023-09-01)

Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm.
af: Su Hyun Lee, et al.
Udgivet: (2023-01-01)

Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
af: Robert Graf, et al.
Udgivet: (2023-11-01)

Deep-Learning-Based Automated Rotator Cuff Tear Screening in Three Planes of Shoulder MRI
af: Kyu-Chong Lee, et al.
Udgivet: (2023-10-01)

MRI radiomics based on deep learning automated segmentation to predict early recurrence of hepatocellular carcinoma
af: Hong Wei, et al.
Udgivet: (2024-05-01)

Automated analysis of heterogeneous catalyst materials using deep learning
af: Treder, KP
Udgivet: (2022)

Automated Diagnosis of Prostate Cancer Using mpMRI Images: A Deep Learning Approach for Clinical Decision Support
af: Anil B. Gavade, et al.
Udgivet: (2023-07-01)

Deep learning system for automated detection of posterior ligamentous complex injury in patients with thoracolumbar fracture on MRI
af: Sang Won Jo, et al.
Udgivet: (2023-11-01)

Automated measurement of anteroposterior diameter and foraminal widths in MRI images for lumbar spinal stenosis diagnosis.
af: Friska Natalia, et al.
Udgivet: (2020-01-01)

Anatomical and functional analysis of cardiac MRI scans using deep learning
af: Xu, H
Udgivet: (2020)

A patch-based deep learning MRI segmentation model for improving efficiency and clinical examination of the spinal tumor
af: Weimin Chen, et al.
Udgivet: (2024-12-01)

Automated Abstractive Text Summarization using Deep Learning
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Udgivet: (2023-01-01)

Automated riverbed composition analysis using deep learning on underwater images
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Udgivet: (2023-11-01)

Empirical Analysis of Automated Stock Trading Using Deep Reinforcement Learning
af: Minseok Kong, et al.
Udgivet: (2023-01-01)