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An artificial neural network for lesion detection on single-photon emission computed tomographic images.

Publication ,  Journal Article
Floyd, CE; Tourassi, GD
Published in: Invest Radiol
September 1992

RATIONALE AND OBJECTIVES: An artificial neural network (ANN) has been developed to detect nonactive circular lesions on single-slice, single-photon emission computed tomographic (SPECT) images reconstructed using filtered back projection (FBP). METHODS: The neural network is a single-layer perception which learns to identify features on the SPECT image using supervised training with a modified delta rule. The network was trained on a set of SPECT images containing clinically realistic levels of noise. The trained network was applied to a set of 120 images, and the detection performance was evaluated at several decision thresholds using receiver operating characteristic (ROC) analysis. RESULTS: The trained neural network performed better than human observers for the same detection task with the same images as reflected by a significantly larger ROC curve area. CONCLUSIONS: ANN can be trained successfully to perform lesion detection on reconstructed SPECT images.

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Published In

Invest Radiol

DOI

ISSN

0020-9996

Publication Date

September 1992

Volume

27

Issue

9

Start / End Page

667 / 672

Location

United States

Related Subject Headings

  • Tomography, Emission-Computed, Single-Photon
  • Software Design
  • ROC Curve
  • Observer Variation
  • Nuclear Medicine & Medical Imaging
  • Neural Networks, Computer
  • Models, Structural
  • Humans
  • Equipment Design
  • 3202 Clinical sciences
 

Citation

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ICMJE
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Floyd, C. E., & Tourassi, G. D. (1992). An artificial neural network for lesion detection on single-photon emission computed tomographic images. Invest Radiol, 27(9), 667–672. https://doi.org/10.1097/00004424-199209000-00001
Floyd, C. E., and G. D. Tourassi. “An artificial neural network for lesion detection on single-photon emission computed tomographic images.Invest Radiol 27, no. 9 (September 1992): 667–72. https://doi.org/10.1097/00004424-199209000-00001.
Floyd, C. E., and G. D. Tourassi. “An artificial neural network for lesion detection on single-photon emission computed tomographic images.Invest Radiol, vol. 27, no. 9, Sept. 1992, pp. 667–72. Pubmed, doi:10.1097/00004424-199209000-00001.

Published In

Invest Radiol

DOI

ISSN

0020-9996

Publication Date

September 1992

Volume

27

Issue

9

Start / End Page

667 / 672

Location

United States

Related Subject Headings

  • Tomography, Emission-Computed, Single-Photon
  • Software Design
  • ROC Curve
  • Observer Variation
  • Nuclear Medicine & Medical Imaging
  • Neural Networks, Computer
  • Models, Structural
  • Humans
  • Equipment Design
  • 3202 Clinical sciences