A Computational Approach Toward Identification of Malignant Lesions of the Human Breast: The Dynamics of Magnetic Resonance Imaging Contrast Agent Uptake

Abstract

Dynamic Gd-DTPA-2 contrast enhanced MRI images are currently used to help identify the malignancy of breast lesions. The time course of contrast agent uptake may thus be a non- invasive method for discriminating benign vs. malignant breast lesions. In this study, a computational technique called fuzzy clustering is employed to empirically categorize voxels of breast MRI images based on the time course of contrast agent enhanced image intensity. Several parameters of the clustering algorithm have been optimized including the fuzzy index and cluster membership thresholds. The clustering algorithm has been able to discriminate contrast uptake heterogeneity within breast lesions, and central vs. peripheral regions. These two features have not, on their own, discriminated malignant vs. benign lesions.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1999
Accession Number
ADA385911

Entities

People

  • John S. Leigh
  • Jonathan H. Kaufman

Organizations

  • University of Pennsylvania

Tags

Communities of Interest

  • Advanced Electronics
  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Cancer
  • Carcinoma
  • Cartilage
  • Data Acquisition
  • Frequency
  • Intensity
  • Magnetic Resonance
  • Magnetic Resonance Imaging
  • Materials
  • Measurement
  • Mechanical Properties
  • Medical Personnel
  • Modulus Of Elasticity
  • Pressure Gradients
  • Radio Frequency
  • Three Dimensional

Readers

  • Medical Imaging.
  • Neural Network Machine Learning.