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

TitleBlob-like feature extraction and matching for brain MR images.
Publication TypeJournal Article
Year of Publication2011
AuthorsRazlighi QR, Stern Y
JournalAnnu Int Conf IEEE Eng Med Biol Soc
Volume2011
Pagination7799-802
Date Published2011
ISSN2694-0604
KeywordsAlgorithms, Brain, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Normal Distribution
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.

DOI10.1109/IEMBS.2011.6091922
Alternate JournalAnnu Int Conf IEEE Eng Med Biol Soc
PubMed ID22256147
PubMed Central IDPMC3971468
Grant ListR01 AG026158 / AG / NIA NIH HHS / United States
T32 AG000261 / AG / NIA NIH HHS / United States
R01 AG26158 / AG / NIA NIH HHS / United States
Related Institute: 
Brain Health Imaging Institute (BHII)

Weill Cornell Medicine
Department of Radiology
525 East 68th Street New York, NY 10065