SpineNetV2: Automated detection, labelling and radiological grading of clinical MR scans

SpineNetV2: Automated detection, labelling and radiological grading of clinical MR scans

This technical report presents SpineNetV2, an automated tool which: (i) detects and labels vertebral bodies in clinical spinal magnetic resonance (MR) scans across a range of commonly used sequences; and (ii) performs radiological grading of lumbar intervertebral discs in T2-weighted scans for a ran...

书目详细资料
Main Authors:	Windsor, R, Jamaludin, A, Kadir, T, Zisserman, A
格式:	Report
语言:	English
出版:	ArXiv 2022

相似书籍

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

External validation of SpineNetV2 on a comprehensive set of radiological features for grading lumbosacral disc pathologies
由: Alemu Sisay Nigru, MSc, et al.
出版: (2024-12-01)

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

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

Context-aware transformers for spinal cancer detection and radiological grading
由: Windsor, R, et al.
出版: (2022)

A convolutional approach to vertebrae detection and labelling in whole spine MRI
由: Windsor, R, et al.
出版: (2020)

SpineNet: automatically pinpointing classification evidence in spinal MRIs
由: Jamaludin, A, et al.
出版: (2016)

Vision-language modelling for radiological imaging and reports in the low data regime
由: Windsor, R, et al.
出版: (2024)

Automated spinal MRI labelling from reports using a large language model
由: Park, RY, et al.
出版: (2024)

Radiological Grading of Spinal MRI
由: Lootus, M, et al.
出版: (2015)

Vertebrae detection and labelling in lumbar MR images
由: Lootus, M, et al.
出版: (2014)

Automated radiological grading of spinal MRIs via weak and self-supervision
由: Windsor, RL
出版: (2023)

ISSLS Prize in Bioengineering Science 2017: Automation of reading of radiological features from magnetic resonance images (MRIs) of the lumbar spine without human intervention is comparable with an expert radiologist.
由: Jamaludin, M, et al.
出版: (2017)

Predicting scoliosis in DXA scans using intermediate representations
由: Jamaludin, A, et al.
出版: (2019)

Predicting scoliosis in DXA scans using intermediate representations
由: Jamaludin, A, et al.
出版: (2019)

Self-supervised multi-modal alignment for whole body medical imaging
由: Windsor, R, et al.
出版: (2021)

Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans
由: Jamaludin, A, et al.
出版: (2023)

Identifying Scoliosis in population-based cohorts: Automation of a validated method based on total body dual energy X-ray absorptiometry scans
由: Jamaludin, A, et al.
出版: (2020)

It's in the bag: stronger supervision for automated face labelling
由: Parkhi, O, et al.
出版: (2015)

Automated video labelling: identifying faces by corroborative evidence
由: Brown, A, et al.
出版: (2021)

MR Morphometry of Lumbar Spine
由: Amit Kumar Choubey, et al.
出版: (2018-04-01)

Update on MR imaging of spondyloarthritis. Part two: spine MR imaging
由: BC Vande Berg, et al.
出版: (2014-07-01)

3D spine shape estimation from single 2D DXA
由: Bourigault, E, et al.
出版: (2024)

Automated video face labelling for films and TV material
由: Parkhi, OM, et al.
出版: (2018)

MR-Guided Radiotherapy for Brain and Spine Tumors
由: Danilo Maziero, et al.
出版: (2021-03-01)

Machine learning based Berlin scoring of magnetic resonance images of the spine in patients with ankylosing spondylitis from the meaure 1 study
由: Jamaludin, A, et al.
出版: (2020)

Ct- and Mr-guided interventions in radiology /
由: Mahnken, Andreas H., et al.
出版: (2009)

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

Automated brain tumor segmentation on multi-modal MR image using SegNet
由: Salma Alqazzaz, et al.
出版: (2019-04-01)

Discriminative semi-Markov models for automated mitotic phase labelling
由: El-Labban, A, et al.
出版: (2012)

DISCRIMINATIVE SEMI-MARKOV MODELS FOR AUTOMATED MITOTIC PHASE LABELLING
由: El-Labban, A, et al.
出版: (2012)

Machine learning-based Berlin scoring of magnetic resonance images of the spine in patients with ankylosing spondylitis: Analysis of data from a phase 3 trial with Secukinumab
由: Jamaludin, A, et al.
出版: (2020)

Classification and Radiological Diagnosis of Thoracolumbar Spine Fractures: WFNS Spine Committee Recommendations
由: Abdul Hafid Bajamal, et al.
出版: (2021-12-01)

Convolutional neural network-based automated segmentation and labeling of the lumbar spine X-ray
由: Sandor Konya, et al.
出版: (2021-01-01)

Manual-protocol inspired technique for improving automated MR image segmentation during label-fusion
由: Nikhil Bhagwat, et al.
出版: (2016-07-01)

Early loosening in CT-scan may suggest low grade infection in revision spine surgery
由: Gemma Vilà-Canet, et al.
出版: (2021-01-01)

Advancing glioma diagnosis: Integrating custom U-Net and VGG-16 for improved grading in MR imaging
由: Sonam Saluja, et al.
出版: (2024-02-01)

AN ANALYSIS OF CLINICO-RADIOLOGICAL AND HISTOPATHOLOGICAL CORRELATION IN TUBERCULOSIS OF SPINE
由: Sadik I Shaikh, et al.
出版: (2013-09-01)

Single-Input Multi-Output U-Net for Automated 2D Foetal Brain Segmentation of MR Images
由: Andrik Rampun, et al.
出版: (2021-10-01)

Fine-Grain Segmentation of the Intervertebral Discs from MR Spine Images Using Deep Convolutional Neural Networks: BSU-Net
由: Sewon Kim, et al.
出版: (2018-09-01)