Evidence map›Paper›PMID 22256147›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2011

Blob-like feature extraction and matching for brain MR images.

Qolamreza R Razlighi, Yaakov Stern

Open access · greenAbstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 82% of its field
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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
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

2 authors at 1 institution in 1 country.

Qolamreza R RazlighiCognitive Neuroscience Division, the Taub Institute, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA. qr2108@columbia.edu
Yaakov Stern
Columbia University · US

Funding

Imaging of Cognition, Learning and Memory in AgingR01AG026158 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STERN, YAAKOV · 2004 to 2021
$10.9M
NEUROPSYCHOLOGY AND COGNITION IN AGINGT32AG000261 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STERN, YAAKOV · 1998 to 2013
$2.1M
NIA NIH HHS R01 AG026158NIA NIH HHS R01 AG26158NIA NIH HHS T32 AG000261
6 · The paper itself

Abstract

The cerebral cortex of the human brain is highly folded. It is useful for neuroscientists and clinical researchers to identify and/or quantify cortical folding patterns across individuals. The top (gyri) and bottom (sulci) of these folds resemble the "blob-like" features used in computer vision. In this article, we evaluate different blob detectors and descriptors on brain MR images, and introduce our own, the "brain blob detector and descriptor (BBDD)." For the first time blob detectors are considered as spatial filters under the scale-space framework and their impulse responses are manipulated for detecting the structures in our interest. The BBDD detector is tailored to the scale and structure of blob-like features that coincide with cortical folds, and its descriptors performed well at discriminating these features in our evaluation.

Indexed as

AlgorithmsBrainHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingNormal Distribution

Identifiers

PMID22256147
PMCPMC3971468
OpenAlexW2153589902

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.