Improving Detection of Axillary Lymph Nodes by Computer-Aided Kinetic Feature Identification in Positron Emission Tomography

Abstract

The goal of this project is to improve detection of metastatic axillary breast cancer through sophisticated physiological modeling and statistical signal processing techniques. The major focus of Year 3 was to improved the feature extraction in visible, primary tumors by adding the factor analysis to the conventional ROI averaging method and to develop the optimal feature-guided filtering criteria for metastasis screening, which were applied to suppress the interference-plus-noise In dynamic data proceeding to the hypothesis test detection. Two types of filters were derived with/without using the physiological features extracted from normal tissues.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2002
Accession Number
ADA412153

Entities

People

  • Xiaoli Yu

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Biomedical Research
  • Cancer
  • Databases
  • Detection
  • Extraction
  • Factor Analysis
  • Feature Extraction
  • Filters
  • Filtration
  • Identification
  • Image Processing
  • Institutional Review Board
  • Metastasis
  • Neoplasms
  • Signal Processing

Readers

  • Medical Imaging.
  • Oncology and Biomarker-Based Cancer Detection.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML