A Novel Fuzzy Topological Approach to the Detection of Mammographic Lesions and Quantification of Parenchymal Density

Abstract

This research focuses on mammographic image processing for the purpose of density quantification, lesion detection and quantification. The approaches are different from those taken in the literature in two respects. (1) They emphasize on identifying the dense regions and analyzing the parenchymal architecture. (2) They use a novel fuzzy connected-ness method of object definition and image segmentation. During this project period, the following have been accomplished: The development and validation of a new method of lesion and density detection based on fuzzy connectedness that utilizes the relative strength of connectedness among objects. The development of a new class of interactive segmentation methods that are more efficient and effective for lesion segmentation than the earlier live wire methods. Further extension of the fuzzy connectedness framework and demonstration of its effectiveness in areas other than mammographic image processing.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2001
Accession Number
ADA392273

Entities

People

  • Jayaram Udupa

Organizations

  • University of Pennsylvania

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Computer Graphics
  • Computer Vision
  • Computers
  • Detection
  • Diagnostic Imaging
  • Electronic Mail
  • Health Services
  • Image Processing
  • Image Segmentation
  • Magnetic Resonance
  • Medical Personnel
  • Recognition
  • Three Dimensional
  • Vascular Diseases
  • X-Ray Computed Tomography

Readers

  • Computer Vision.
  • Oncology and Biomarker-Based Cancer Detection.