Improving Cancer Detection and Dose Efficiency in Dedicated Breast Cancer CT

Abstract

Breast cancer is the second leading cause of cancer mortality among women in the United States. Dedicated breast computed tomography (CT) has been developed for potential use as an imaging tool for breast-cancer screening or diagnosis, because it can yield three-dimensional(3D) volumetric images of the breast, thus overcoming inherent limitations of conventional two-dimensional(2D) mammography. Image quality and the radiation dose are of important concerns in breast CT imaging. The objective of this project is to investigate and develop innovative imaging configurations and reconstruction algorithms for obtaining accurate images and reducing radiation dose in breast CT imaging. During the second year of this project, I have continued the investigation of innovative imaging configuration and have implemented reconstruction algorithms considering different imaging configurations. I have also studied the application of total variation(TV)-based algorithm to sparse view reconstruction and have developed various methods to evaluate reconstruction-image quality. In summary, during the second year, I have successfully carried out research on the planned tasks, and the results obtained have formed a solid basis for me to continue the research planned for the next year.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2011
Accession Number
ADA543105

Entities

People

  • Junguo Bian

Organizations

  • University of Chicago

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Compressed Sensing
  • Data Acquisition
  • Data Sets
  • Department Of Defense
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Image Reconstruction
  • Linear Systems
  • Power Spectra
  • Three Dimensional
  • Tomography
  • Two Dimensional
  • Visual Inspection
  • X Rays
  • X-Ray Computed Tomography

Fields of Study

  • Medicine
  • Physics

Readers

  • Medical Imaging.
  • Oncology and Biomarker-Based Cancer Detection.
  • Systems Analysis and Design