Preventing Signal Degradation During Elastic Matching of Noisy DCE-MR Eye Images View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2006

AUTHORS

Kishore Mosaliganti , Guang Jia , Johannes Heverhagen , Raghu Machiraju , Joel Saltz , Michael Knopp

ABSTRACT

Motion during the acquisition of dynamic contrast enhanced MRI can cause model-fitting errors requiring co-registration. Clinical implementations use a pharmacokinetic model to determine lesion parameters from the contrast passage. The input to the model is the time-intensity plot from a region of interest (ROI) covering the lesion extent. Motion correction meanwhile involves interpolation and smoothing operations thereby affecting the time-intensity plots. This paper explores the trade-offs in applying an elastic matching procedure on the lesion detection and proposes enhancements. The method of choice is the 3D realization of the Demon's elastic matching procedure. We validate our enhancements using synthesized deformation of stationary datasets that also serve as ground-truth. The framework is tested on 42 human eye datasets. Hence, we show that motion correction is beneficial in improving the model-fit and yet needs enhancements to correct for the intensity reductions during parameter estimation. More... »

PAGES

832-839

References to SciGraph publications

  • 2005. Tracer Kinetic Model-Driven Registration for Dynamic Contrast Enhanced MRI Time Series in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2005
  • 1996. Cross validation of three inter-patients matching methods in VISUALIZATION IN BIOMEDICAL COMPUTING
  • 1998. The correlation ratio as a new similarity measure for multimodal image registration in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION — MICCAI’98
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/11866565_102

    DOI

    http://dx.doi.org/10.1007/11866565_102

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1038906148

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/17354968


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