Modeling normal brain asymmetry in MR images applied to anomaly detection without segmentation and data annotation

Samuel Botter Martins; Barbara Caroline Benato; Bruna Ferreira Silva; Clarissa Lyn Yasuda; Alexandre Xavier Falcão

doi:10.1117/12.2512873

13 March 2019 Modeling normal brain asymmetry in MR images applied to anomaly detection without segmentation and data annotation

Samuel Botter Martins, Barbara Caroline Benato, Bruna Ferreira Silva, Clarissa Lyn Yasuda, Alexandre Xavier Falcão

Author Affiliations +

Proceedings Volume 10950, Medical Imaging 2019: Computer-Aided Diagnosis; 109500C (2019) https://doi.org/10.1117/12.2512873
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

While the human brain presents natural structural asymmetries between left and right hemispheres in MR images, most neurological diseases are associated with abnormal brain asymmetries. Due to the great variety of such anomalies, we present a framework to model normal structural brain asymmetry from control subjects only, independent of the neurological disease. The model dismisses data annotation by exploiting generative deep neural networks and one-class classifiers. We also propose a patch-based model to localize volumes of interest with reduced background sizes around selected brain structures and a one-class classifier based on an optimum-path forest. This model makes the framework independent of segmentation, which may fail, especially in abnormal images, or may not be available for a given structure. We validate the first method to the detection of abnormal hippocampal asymmetry using distinct groups of Epilepsy patients and testing controls. The results of validation using the original feature space and a two-dimensional space based on non-linear projection show the potential to extend the framework for abnormal asymmetry detection in other parts of the brain and develop intelligent and interactive virtual environments. For instance, the approach can be used for screening, inspection, and annotation of the detected anomaly type, allowing the development of CADx systems.

Conference Presentation

Citation Download Citation

Samuel Botter Martins, Barbara Caroline Benato, Bruna Ferreira Silva, Clarissa Lyn Yasuda, and Alexandre Xavier Falcão "Modeling normal brain asymmetry in MR images applied to anomaly detection without segmentation and data annotation", Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 109500C (13 March 2019); https://doi.org/10.1117/12.2512873

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available