Pattern visualization and recognition using tensor factorization for early differential diagnosis of parkinsonism

Rui Li, Ping Wu, Igor Yakushev, Jian Wang, Sibylle I. Ziegler, Stefan Förster, Sung Cheng Huang, Markus Schwaiger, Nassir Navab, Chuantao Zuo, Kuangyu Shi

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

3 Zitate (Scopus)

Abstract

Idiopathic Parkinsons disease (PD) and atypical parkinsonian syndromes may have similar symptoms at the early disease stage. Pattern recognition on metabolic imaging has been confirmed of distinct value in the early differential diagnosis of Parkinsonism. However, the principal component analysis (PCA) based method ends up with a unique probability score of each disease pattern. This restricts the exploration of heterogeneous characteristic features for differentiation. There is no visualization of the underlying mechanism to assist the radiologist/neurologist either. We propose a tensor factorization based method to extract the characteristic patterns of the diseases. By decomposing the 3D data, we can capture the intrinsic characteristic pattern in the data. In particular, the disease-related patterns can be visualized individually for the inspection by physicians. The test on PET images of 206 early parkinsonian patients has confirmed differential patterns on the visualized feature images using the proposed method. Computer-aided diagnosis based on multi-class support vector machine (SVM) shown improved diagnostic accuracy of Parkinsonism using the tensor-factorized feature images compared to the state-of-the-art PCA-based scores [Tang et al. Lancet Neurol. 2010].

OriginalspracheEnglisch
TitelMedical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings
Redakteure/-innenLena Maier-Hein, Alfred Franz, Pierre Jannin, Simon Duchesne, Maxime Descoteaux, D. Louis Collins
Herausgeber (Verlag)Springer Verlag
Seiten125-133
Seitenumfang9
ISBN (Print)9783319661780
DOIs
PublikationsstatusVeröffentlicht - 2017
Veranstaltung20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 - Quebec City, Kanada
Dauer: 11 Sept. 201713 Sept. 2017

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band10435 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Konferenz

Konferenz20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017
Land/GebietKanada
OrtQuebec City
Zeitraum11/09/1713/09/17

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