Use of A'Scape for theDetection of Lung Tumors.

Abstract

The Automatic Statistical characterization and Partitioning of Environment (A'SCAPE) has previously been successfully used to characterize infrared (IR) and radar land scenes as a target predetection state (DoD application) and, in another application (law enforcement), to detect weapons concealed underneath clothing in scenes collected by different types of sensors including IR and Millimeter-wave sensors. In this dual-use technology project, the prime emphasis was placed on structuring A'SCAPE to (1) detect tumors in lung tissue, and (2) classify a particular tumor as being either benign or malignant wing computer tomography (CT) data. It is shown that A'SCAPB (1) can successfully highlight suspected tumor tissue within the lung image, and (2) has the potential to detect and classify tumors. The latter point can be proven however only if more data of both benign and malignant tumors is made available. During this effort, a library of only 5 usable data sets were available. Two of these sets are wed to develop rules and the remaining three are used to test the rules. However, the results demonstrate promise for future application of this approach.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1998
Accession Number
ADA357185

Entities

People

  • Mohamed A. Slamani

Tags

Communities of Interest

  • Biomedical
  • Sensors

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Cancer
  • Composite Images
  • Data Science
  • Data Sets
  • Detection
  • Diagnostic Imaging
  • Goodness Of Fit Tests
  • Information Processing
  • Information Science
  • Monte Carlo Method
  • Power Levels
  • Probability
  • Probability Distributions
  • Statistical Algorithms
  • Statistical Distributions
  • X-Ray Computed Tomography

Readers

  • Medical Imaging.
  • Neural Network Machine Learning.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • 5G
  • 5G - DoD 5G Program