Identification of cerebral small vessel disease using multiple instance learning

Chen L, Tong T, Ho CP, Patel R, Cohen D, Dawson AC, Halse O, Geraghty O, Rinne PEM, White CJ, Nakornchai T, Bentley P, Rueckert D (2015)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2015

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Series: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Book Volume: 9349

Pages Range: 523-530

DOI: 10.1007/978-3-319-24553-9_64

Abstract

Cerebral small vessel disease (SVD) is a common cause of ageing-associated physical and cognitive impairment. Identifying SVD is important for both clinical and research purposes but is usually dependent on radiologists’ evaluation of brain scans. Computer tomography (CT) is the most widely used brain imaging technique but for SVD it shows a low signal-to-noise ratio, and consequently poor inter-rater reliability. We therefore propose a novel framework based on multiple instance learning (MIL) to distinguish between absent/mild SVD and moderate/severe SVD. Intensity patches are extracted from regions with high probability of containing lesions. These are then used as instances in MIL for the identification of SVD. A large baseline CT dataset, consisting of 590 CT scans, was used for evaluation. We achieved approximately 75% accuracy in classifying two different types of SVD, which is high for this challenging problem. Our results outperform those obtained by either standard machine learning methods or current clinical practice.

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB) The Griffin Institute - Northwick Park Institute for Medical Research (NPIMR) GB United Kingdom (GB) Hammersmith Hospital GB United Kingdom (GB)

How to cite

APA:

Chen, L., Tong, T., Ho, C.P., Patel, R., Cohen, D., Dawson, A.C.,... Rueckert, D. (2015). Identification of cerebral small vessel disease using multiple instance learning. In (pp. 523-530). Springer Verlag.

MLA:

Chen, Liang, et al. "Identification of cerebral small vessel disease using multiple instance learning." Springer Verlag, 2015. 523-530.

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