A novel cortical thickness estimation method based on volumetric Laplace-Beltrami operator and heat kernel

for the Alzheimer's Disease Neuroimaging Initiative

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Cortical thickness estimation in magnetic resonance imaging (MRI) is an important technique for research on brain development and neurodegenerative diseases. This paper presents a heat kernel based cortical thickness estimation algorithm, which is driven by the graph spectrum and the heat kernel theory, to capture the gray matter geometry information from the in vivo brain magnetic resonance (MR) images. First, we construct a tetrahedral mesh that matches the MR images and reflects the inherent geometric characteristics. Second, the harmonic field is computed by the volumetric Laplace-Beltrami operator and the direction of the steamline is obtained by tracing the maximum heat transfer probability based on the heat kernel diffusion. Thereby we can calculate the cortical thickness information between the point on the pial and white matter surfaces. The new method relies on intrinsic brain geometry structure and the computation is robust and accurate. To validate our algorithm, we apply it to study the thickness differences associated with Alzheimer's disease (AD) and mild cognitive impairment (MCI) on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Our preliminary experimental results on 151 subjects (51 AD, 45 MCI, 55 controls) show that the new algorithm may successfully detect statistically significant difference among patients of AD, MCI and healthy control subjects. Our computational framework is efficient and very general. It has the potential to be used for thickness estimation on any biological structures with clearly defined inner and outer surfaces.

Original languageEnglish (US)
Pages (from-to)1-20
Number of pages20
JournalMedical Image Analysis
Volume22
Issue number1
DOIs
StatePublished - May 1 2015

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Mathematical operators
Alzheimer Disease
Magnetic resonance
Hot Temperature
Brain
Magnetic Resonance Spectroscopy
Neurodegenerative diseases
Neuroimaging
Geometry
Brain Diseases
Neurodegenerative Diseases
Healthy Volunteers
Research Design
Magnetic Resonance Imaging
Heat transfer
Imaging techniques
Cognitive Dysfunction

Keywords

  • Cortical thickness
  • False discovery rate
  • Heat kernel
  • Spectral analysis
  • Tetrahedral mesh

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Radiology Nuclear Medicine and imaging
  • Health Informatics
  • Radiological and Ultrasound Technology

Cite this

A novel cortical thickness estimation method based on volumetric Laplace-Beltrami operator and heat kernel. / for the Alzheimer's Disease Neuroimaging Initiative.

In: Medical Image Analysis, Vol. 22, No. 1, 01.05.2015, p. 1-20.

Research output: Contribution to journalArticle

for the Alzheimer's Disease Neuroimaging Initiative. / A novel cortical thickness estimation method based on volumetric Laplace-Beltrami operator and heat kernel. In: Medical Image Analysis. 2015 ; Vol. 22, No. 1. pp. 1-20.
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