DeepAI AI Chat
Log In Sign Up

Osteoporotic and Neoplastic Compression Fracture Classification on Longitudinal CT

01/27/2016
by   Yinong Wang, et al.
0

Classification of vertebral compression fractures (VCF) having osteoporotic or neoplastic origin is fundamental to the planning of treatment. We developed a fracture classification system by acquiring quantitative morphologic and bone density determinants of fracture progression through the use of automated measurements from longitudinal studies. A total of 250 CT studies were acquired for the task, each having previously identified VCFs with osteoporosis or neoplasm. Thirty-six features or each identified VCF were computed and classified using a committee of support vector machines. Ten-fold cross validation on 695 identified fractured vertebrae showed classification accuracies of 0.812, 0.665, and 0.820 for the measured, longitudinal, and combined feature sets respectively.

READ FULL TEXT

page 2

page 4

03/20/2020

Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods

This study presents early phase detection of Coronavirus (COVID-19), whi...
02/10/2020

Validation and Optimization of Multi-Organ Segmentation on Clinical Imaging Archives

Segmentation of abdominal computed tomography(CT) provides spatial conte...
02/16/2020

Image Entropy for Classification and Analysis of Pathology Slides

Pathology slides of lung malignancies are classified using the "Salient ...
06/29/2019

Improved ICH classification using task-dependent learning

Head CT is one of the most commonly performed imaging studied in the Eme...