title: A Feature-Based Approach to Big Data Analysis of Medical Images.
abstract: This paper proposes an inference method well-suited to large sets of medical images. The method is based upon a framework where distinctive 3D scale-invariant features are indexed efficiently to identify approximate nearest-neighbor (NN) feature matches-in O (log N) computational complexity in the number of images N. It thus scales well to large data sets, in contrast to methods based on pair-wise image registration or feature matching requiring O(N) complexity. Our theoretical contribution is a density estimator based on a generative model that generalizes kernel density estimation and K-nearest neighbor (KNN) methods.. The estimator can be used for on-the-fly queries, without requiring explicit parametric models or an off-line training phase. The method is validated on a large multi-site data set of 95,000,000 features extracted from 19,000 lung CT scans. Subject-level classification identifies all images of the same subjects across the entire data set despite deformation due to breathing state, including unintentional duplicate scans. State-of-the-art performance is achieved in predicting chronic pulmonary obstructive disorder (COPD) severity across the 5-category GOLD clinical rating, with an accuracy of 89% if both exact and one-off predictions are considered correct.
authors.forename: Matthew
authors.initials: M
authors.lastname: Toews
authors.forename: Christian
authors.initials: C
authors.lastname: Wachinger
authors.forename: Raul San Jose
authors.initials: RS
authors.lastname: Estepar
authors.forename: William M
authors.initials: WM
authors.lastname: Wells
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging; D010363:Pattern Recognition, Automated / Q000379:methods*; D029424:Pulmonary Disease, Chronic Obstructive / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*