Title
Small white matter lesion detection in cerebral small vessel disease
Abstract
Cerebral small vessel disease (SVD) is a common finding on magnetic resonance images of elderly people. White matter lesions (WML) are important markers for not only the small vessel disease, but also neuro-degenerative diseases including multiple sclerosis, Alzheimer's disease and vascular dementia. Volumetric measurements such as the "total lesion load", have been studied and related to these diseases. With respect to SVD we conjecture that small lesions are important, as they have been observed to grow over time and they form the majority of lesions in number. To study these small lesions they need to be annotated, which is a complex and time-consuming task. Existing (semi) automatic methods have been aimed at volumetric measurements and large lesions, and are not suitable for the detection of small lesions. In this research we established a supervised voxel classification CAD system, optimized and trained to exclusively detect small WMLs. To achieve this, several preprocessing steps were taken, which included a robust standardization of subject intensities to reduce inter-subject intensity variability as much as possible. A number of features that were found to be well identifying small lesions were calculated including multimodal intensities, tissue probabilities, several features for accurate location description, a number of second order derivative features as well as multi-scale annular filter for blobness detection. Only small lesions were used to learn the target concept via Adaboost using random forests as its basic classifiers. Finally the results were evaluated using Free-response receiver operating characteristic.
Year
DOI
Venue
2015
10.1117/12.2081597
Proceedings of SPIE
Keywords
Field
DocType
small white matter lesions,white matter hyperintensities,computer aided detection,small vessel disease
Voxel,Computer vision,Receiver operating characteristic,AdaBoost,White matter,Lesion,Vascular dementia,Artificial intelligence,Random forest,Hyperintensity,Physics
Conference
Volume
ISSN
Citations 
9414
0277-786X
2
PageRank 
References 
Authors
0.43
4
7
Name
Order
Citations
PageRank
Mohsen Ghafoorian168127.23
Nico Karssemeijer2992122.49
i van uden3241.63
Frank-Erik de Leeuw4543.84
Tom Heskes51519198.44
Elena Marchiori61272164.66
Bram Platel724521.42