Image Processing to Improve Detection of Mesial Temporal Sclerosis in Adults.

F Dahi Matthew S Parsons H L P Orlowski Salter Amber Jeffrey R Millman Aseem Sharma

Published in: AJNR. American journal of neuroradiology (2019)

In this retrospective case-control study, we investigated whether an image-processing algorithm designed to exaggerate the intensity of diseased hippocampi on FLAIR images can improve the diagnostic accuracy and interobserver reliability of radiologists in detecting mesial temporal sclerosis-related hippocampal signal alteration. Herein, we share the results of this study that showed that the image processing improved the confidence of radiologists in detecting mesial temporal sclerosis-related signal alteration, allowing an improved sensitivity, specificity, and interobserver reliability.

Keyphrases

temporal lobe epilepsy
deep learning
artificial intelligence
convolutional neural network
machine learning
high intensity
optical coherence tomography
loop mediated isothermal amplification
mass spectrometry
drug induced