Computer-Aided Diagnosis and Feature-Guided Data Reduction Systems in Mammography

Abstract

The goals of this project are: (1) Implement and evaluate a computer-aided diagnosis (CAD) system to assist radiologists in mammographic interpretation. (2) Develop and evaluate a feature-guided data compression technique to facilitate implementation of digital mammography. For the first sub-project, we plan to implement our CAD algorithms for detection and classification of microcalcifications in a high speed workstation, develop user interface for efficient operation of the CAD programs, and perform a pilot clinical trial. For the second sub-project, we plan to evaluate and select the most efficient lossless and lossy data compression techniques that can provide maximum compression ratio without noticeable loss of information for mammography. In the second year of the funding period, we have performed the following studies: (1) completion of the graphical user interface (GUl) development based on a PC which is networked to the CAD system, (2) improvement and implementation of the mass detection program in the CAD system, (3) continue the improvement and implementation of the microcalcification detection program, (4) quantitative evaluation of the data compression methods for mammograms, and (5) design methods and programs for data collection and data analysis for the pilot clinical trial. These studies are the necessary steps to accomplish the goals of this project.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1998
Accession Number
ADA361648

Entities

People

  • Heang-Ping Chan

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Algorithms
  • Breast Cancer
  • Clinical Trials
  • Compression Ratio
  • Computer Vision
  • Computer-Aided Diagnosis
  • Computers
  • Data Compression
  • Detection
  • Diagnostic Imaging
  • Graphical User Interface
  • Health Services
  • Image Processing
  • Medical Personnel
  • Operating Systems
  • Pattern Recognition
  • User Interface

Fields of Study

  • Medicine
  • Physics

Readers

  • Database Systems and Applications
  • Oncology and Biomarker-Based Cancer Detection.