Blob-like feature extraction and matching for brain MR images. Academic Article uri icon

Overview

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.

publication date

  • January 1, 2011

Research

keywords

  • Algorithms
  • Brain
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging

Identity

PubMed Central ID

  • PMC3971468

Scopus Document Identifier

  • 84861686583

Digital Object Identifier (DOI)

  • 10.1109/IEMBS.2011.6091922

PubMed ID

  • 22256147

Additional Document Info

volume

  • 2011