Convolutional Neural Networks based automated segmentation and labelling of the lumbar spine X-ray

2020-04-04 · Sandor Konya, Sai Natarajan T R, Hassan Allouch, Kais Abu Nahleh, Omneya Yakout Dogheim, Heinrich Boehm

The aim of this study is to investigate the segmentation accuracies of different segmentation networks trained on 730 manually annotated lateral lumbar spine X-rays. Instance segmentation networks were compared to semantic segmentation networks. The study cohort comprised diseased spines and postoperative images with metallic implants. The average mean accuracy and mean intersection over union (IoU) was up to 3 percent better for the best performing instance segmentation model, the average pixel accuracy and weighted IoU were slightly better for the best performing semantic segmentation model. Moreover, the inferences of the instance segmentation models are easier to implement for further processing pipelines in clinical decision support.

📄 PDF Abstract BibTeX arXiv:2004.03364

Code (0)

등록된 구현이 없습니다.

Tasks

Instance Segmentation Segmentation Semantic Segmentation

A Convolutional Approach to Vertebrae Detection and Labelling in Whole Spine MRI

2020-07-06 · Rhydian Windsor, Amir Jamaludin, Timor Kadir, Andrew Zisserman

We propose a novel convolutional method for the detection and identification of vertebrae in whole spine MRIs. This involves using a learnt vector field to group detected vertebrae corners together into individual verteb…

Image-to-Image Translation Translation

SymTC: A Symbiotic Transformer-CNN Net for Instance Segmentation of Lumbar Spine MRI

2024-01-17 · Jiasong Chen, Linchen Qian, Linhai Ma, Timur Urakov 외

Intervertebral disc disease, a prevalent ailment, frequently leads to intermittent or persistent low back pain, and diagnosing and assessing of this disease rely on accurate measurement of vertebral bone and intervertebr…

Data Augmentation Image Segmentation Instance Segmentation Segmentation+1

SpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scans

2022-05-03 · Rhydian Windsor, Amir Jamaludin, Timor Kadir, Andrew Zisserman

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 ra…

Body Detection

Panoptic Segmentation and Labelling of Lumbar Spine Vertebrae using Modified Attention Unet

2024-04-28 · Rikathi Pal, Priya Saha, Somoballi Ghoshal, Amlan Chakrabarti 외

Segmentation and labeling of vertebrae in MRI images of the spine are critical for the diagnosis of illnesses and abnormalities. These steps are indispensable as MRI technology provides detailed information about the tis…

Panoptic Segmentation Segmentation

Attention-based Shape-Deformation Networks for Artifact-Free Geometry Reconstruction of Lumbar Spine from MR Images

2024-03-30 · Linchen Qian, Jiasong Chen, Linhai Ma, Timur Urakov 외

Lumbar disc degeneration, a progressive structural wear and tear of lumbar intervertebral disc, is regarded as an essential role on low back pain, a significant global health concern. Automated lumbar spine geometry reco…

Image Segmentation Semantic Segmentation