Opportunities for Mining Radiology Archives for Pediatric Control Images

12/07/2017
by   Camilo Bermudez, et al.
0

A large database of brain imaging data from healthy, normal controls is useful to describe physiologic and pathologic structural changes at a population scale. In particular, these data can provide information about structural changes throughout development and aging. However, scarcity of control data as well as technical challenges during imaging acquisition has made it difficult to collect large amounts of data in a healthy pediatric population. In this study, we search the medical record at Vanderbilt University Medical Center for pediatric patients who received brain imaging, either CT or MRI, according to 7 common complaints: headache, seizure, altered level of consciousness, nausea and vomiting, dizziness, head injury, and gait abnormalities in order to find the percent of studies that demonstrated pathologic findings. Using a text-search based algorithm, we show that an average of 59.3 resulting in the production of thousands of normal images. These results suggest there is a wealth of pediatric imaging control data which can be used to create normative descriptions of development as well as to establish biomarkers for disease.

READ FULL TEXT

page 6

page 7

research
07/22/2016

Classification of Alzheimer's Disease Structural MRI Data by Deep Learning Convolutional Neural Networks

Recently, machine learning techniques especially predictive modeling and...
research
04/10/2021

Deep Learning Identifies Neuroimaging Signatures of Alzheimer's Disease Using Structural and Synthesized Functional MRI Data

Current neuroimaging techniques provide paths to investigate the structu...
research
12/06/2019

MRI correlates of chronic symptoms in mild traumatic brain injury

Veterans with mild traumatic brain injury (mTBI) have reported auditory ...
research
03/28/2023

SynthRAD2023 Grand Challenge dataset: generating synthetic CT for radiotherapy

Purpose: Medical imaging has become increasingly important in diagnosing...
research
08/22/2023

Characterizing normal perinatal development of the human brain structural connectivity

Early brain development is characterized by the formation of a highly or...
research
04/18/2019

Alterations in Structural Correlation Networks with Prior Concussion in Collision-Sport Athletes

Several studies have used structural correlation networks, derived from ...
research
05/11/2023

Revealing Patterns of Symptomatology in Parkinson's Disease: A Latent Space Analysis with 3D Convolutional Autoencoders

This work proposes the use of 3D convolutional variational autoencoders ...

Please sign up or login with your details

Forgot password? Click here to reset