MRI white matter lesion segmentation using an ensemble of neural networks and overcomplete patch-based voting

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
José V ManjónOlivier Salvado

Abstract

Accurate quantification of white matter hyperintensities (WMH) from Magnetic Resonance Imaging (MRI) is a valuable tool for the analysis of normal brain ageing or neurodegeneration. Reliable automatic extraction of WMH lesions is challenging due to their heterogeneous spatial occurrence, their small size and their diffuse nature. In this paper, we present an automatic method to segment these lesions based on an ensemble of overcomplete patch-based neural networks. The proposed method successfully provides accurate and regular segmentations due to its overcomplete nature while minimizing the segmentation error by using a boosted ensemble of neural networks. The proposed method compared favourably to state of the art techniques using two different neurodegenerative datasets.

Citations

Jan 8, 2020·Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring·Christa DangUNKNOWN AIBL Research Group
Feb 20, 2020·Current Opinion in Neurology·Sepehr Golriz KhatamiMartin Hofmann-Apitius
Sep 29, 2020·Journal of Alzheimer's Disease : JAD·Ying XiaUNKNOWN AIBL Research Group
Jan 29, 2021·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Ramya BalakrishnanAndrew J Farrall
Jun 4, 2021·Scientific Reports·Subhranil KoleyIman Aganj

❮ Previous
Next ❯

Related Concepts

Related Feeds

Brain Aging

Here is the latest research on intrinsic and extrinsic factors, as well as pathways and mechanisms that underlie aging in the central nervous system.