Detection of vertebral fractures in CT using 3D Convolutional Neural Networks

11/05/2019
by   Joeri Nicolaes, et al.
13

Osteoporosis induced fractures occur worldwide about every 3 seconds. Vertebral compression fractures are early signs of the disease and considered risk predictors for secondary osteoporotic fractures. We present a detection method to opportunistically screen spine-containing CT images for the presence of these vertebral fractures. Inspired by radiology practice, existing methods are based on 2D and 2.5D features but we present, to the best of our knowledge, the first method for detecting vertebral fractures in CT using automatically learned 3D feature maps. The presented method explicitly localizes these fractures allowing radiologists to interpret its results. We train a voxel-classification 3D Convolutional Neural Network (CNN) with a training database of 90 cases that has been semi-automatically generated using radiologist readings that are readily available in clinical practice. Our 3D method produces an Area Under the Curve (AUC) of 95 detection and an AUC of 93 five-fold cross-validation experiment.

READ FULL TEXT

page 6

page 10

page 11

research
01/30/2021

Detecting Pulmonary Coccidioidomycosis (Valley fever) with Deep Convolutional Neural Networks

Coccidioidomycosis is the most common systemic mycosis in dogs in the so...
research
10/08/2020

3D Convolutional Sequence to Sequence Model for Vertebral Compression Fractures Identification in CT

An osteoporosis-related fracture occurs every three seconds worldwide, a...
research
04/14/2022

Interpretable Vertebral Fracture Quantification via Anchor-Free Landmarks Localization

Vertebral body compression fractures are early signs of osteoporosis. Th...
research
05/25/2020

Keypoints Localization for Joint Vertebra Detection and Fracture Severity Quantification

Vertebral body compression fractures are reliable early signs of osteopo...
research
06/06/2017

Compression Fractures Detection on CT

The presence of a vertebral compression fracture is highly indicative of...
research
10/10/2017

Application of Deep Learning in Neuroradiology: Automated Detection of Basal Ganglia Hemorrhage using 2D-Convolutional Neural Networks

Background: Deep learning techniques have achieved high accuracy in imag...
research
08/17/2021

Neonatal Bowel Sound Detection Using Convolutional Neural Network and Laplace Hidden Semi-Markov Model

Abdominal auscultation is a convenient, safe and inexpensive method to a...

Please sign up or login with your details

Forgot password? Click here to reset