Few-View Tomographic Reconstruction of Technetium-99m-Sestamibi Distribution for the Detection and Differentiation of Breast Lesions

Abstract

Scintimammography (SMM) is a nuclear medicine test with the potential to provide relatively low-cost, minimally invasive differentiation of breast abnormalities detected by physical examination or mammography. While the most widely used clinical protocol involves acquiring one or two planar views, occasionally supplemented by conventional SPECT, we have established that a dedicated breast SPECT geometry, in which the camera revolves around the breast alone, would provide superior lesion detectability to these other two approaches. Because the time required by tomographic studies to acquire data useful to popular reconstruction algorithms might be excessive for SPECT SMM, we have worked to develop reconstruction algorithms that can generate diagnostically useful SMM images from a smaller number of views than is usually used. In particular, we have developed a technique in which the few-view sinogram is first smoothed using a spline-based, Bayesian technique and then additional views are interpolated using periodic spline interpolation. The spline interpolation approach was chosen after extensive investigation of the accuracy and noise properties of various periodic interpolation approaches. We find that with use of this technique, diagnostically meaningful dedicated SPECT SMM images can be reconstructed from as few as 15 projection views.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2000
Accession Number
ADA388601

Entities

People

  • Chin-tu Chen
  • Patrick La Riviere

Organizations

  • University of Chicago

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Breast Cancer
  • Cancer
  • Computational Science
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Geometry
  • Health Services
  • Information Processing
  • Medical Personnel
  • Random Variables
  • Three Dimensional
  • Tomography
  • Two Dimensional
  • X-Ray Computed Tomography

Fields of Study

  • Physics

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Medical Imaging.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference