Evidence map›Paper›PMID 30328551›Full record

ArticleNeuroinformatics2019

The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease.

Alexandre Yukio Yamashita, Alexandre Xavier Falcão, Neucimar Jerônimo Leite, Alzheimer’s Disease Neuroimaging Initiative

Abstract read
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In one paragraph

Article in Neuroinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alexandre Yukio YamashitaDepartamento de Software B, Instituto de Pesquisas Eldorado, Campinas, Brazil. alexandre.yamashita@eldorado.org.br.ORCID http://orcid.org/0000-0001-6427-6143
Alexandre Xavier FalcãoInstitute of Computing, University of Campinas, Campinas, Brazil.
Neucimar Jerônimo LeiteInstitute of Computing, University of Campinas, Campinas, Brazil.
Alzheimer’s Disease Neuroimaging Initiative

Funding

CNPq 302970/2014-2FAPESP 14/12236-1
6 · The paper itself

Abstract

A crucial quest in neuroimaging is the discovery of image features (biomarkers) associated with neurodegenerative disorders. Recent works show that such biomarkers can be obtained by image analysis techniques. However, these techniques cannot be directly compared since they use different databases and validation protocols. In this paper, we present an extensive study of image descriptors for the diagnosis of Alzheimer Disease (AD) and introduce a new one, named Residual Center of Mass (RCM). The RCM descriptor explores image moments and other techniques to enhance brain regions and select discriminative features for the diagnosis of AD. For validation, a Support Vector Machine (SVM) is trained with the selected features to classify images from normal subjects and patients with AD. We show that RCM with SVM achieves the best accuracies on a considerable number of exams by 10-fold cross-validation - 95.1% on 507 FDG-PET scans and 90.3% on 1374 MRI scans.

Indexed as

Support Vector MachineAgedAlzheimer DiseaseBrainDatabases, FactualFemaleHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingMaleNeuroimagingPositron-Emission TomographyAlzheimer diseaseBiomarkerDiagnosisImage analysisMachine learningNeuroimagingSupport vector machine

Identifiers

PMID30328551

What OpenQuestion holds

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Registered trials

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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.