ArticleMedical computer vision and Bayesian and graphical models for biomedical imaging : MICCAI 2016 international workshop, MCV and BAMBI, Athens, Greece, October 21, 2016 : revised selected papers2016
Landmark-Based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images.
Article in Medical computer vision and Bayesian and graphical models for biomedical imaging : MICCAI 2016 international workshop, MCV and BAMBI, Athens, Greece, October 21, 2016 : revised selected papers, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- A classification for complex imbalanced data in disease screening and early diagnosis.Statistics in medicine · 2022Article
- Computer-Aided Multi-Target Management of Emergent Alzheimer's Disease.Bioinformation · 2018Article
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Authors and funding
5 authors.
Funding
Abstract
In this paper, we propose a landmark-based feature extraction method for AD diagnosis using longitudinal structural MR images, which requires no nonlinear registration or tissue segmentation in the application stage and is robust to the inconsistency among longitudinal scans. Specifically, (1) the discriminative landmarks are first automatically discovered from the whole brain, which can be efficiently localized using a fast landmark detection method for the testing images; (2) High-level statistical spatial features and contextual longitudinal features are then extracted based on those detected landmarks. Using the spatial and longitudinal features, a linear support vector machine (SVM) is adopted for distinguishing AD subjects from healthy controls (HCs) and also mild cognitive impairment (MCI) subjects from HCs, respectively. Experimental results demonstrate the competitive classification accuracies, as well as a promising computational efficiency.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.