A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis
Abstract
Digital tomosynthesis mammography (DTM) is a promising new modality for breast cancer detection. In DTM, projection-view images are acquired at a limited number of angles over a limited angular range and the imaged volume is reconstructed from the two-dimensional projections, thus providing three-dimensional structural information of the breast tissue. In this work, we investigated three representative reconstruction methods for this limited-angle cone-beam tomographic problem, including the backprojection (BP) method, the simultaneous algebraic reconstruction technique (SART) and the maximum likelihood method with the convex algorithm (ML-convex). The SART and ML-convex methods were both initialized with BP results to achieve efficient reconstruction. A second generation GE prototype tomosynthesis mammography system with a stationary digital detector was used for image acquisition. Projection-view images were acquired from 21 angles in 3 deg. increments over a {+-}30 deg. angular range. We used an American College of Radiology phantom and designed three additional phantoms to evaluate the image quality and reconstruction artifacts. In addition to visual comparison of the reconstructed images of different phantom sets, we employed the contrast-to-noise ratio (CNR), a line profile of features, an artifact spread function (ASF), a relative noise power spectrum (NPS), and a line object spread function (LOSF) to quantitativelymore »
- Authors:
-
- Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109-0904 (United States)
- Publication Date:
- OSTI Identifier:
- 20853597
- Resource Type:
- Journal Article
- Journal Name:
- Medical Physics
- Additional Journal Information:
- Journal Volume: 33; Journal Issue: 10; Other Information: DOI: 10.1118/1.2237543; (c) 2006 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 62 RADIOLOGY AND NUCLEAR MEDICINE; ALGORITHMS; BEAMS; BIOMEDICAL RADIOGRAPHY; CARCINOMAS; IMAGE PROCESSING; IMAGES; ITERATIVE METHODS; MAMMARY GLANDS; MAXIMUM-LIKELIHOOD FIT; NOISE; PHANTOMS; TOMOGRAPHY; X-RAY SOURCES
Citation Formats
Yiheng, Zhang, Chan, H -P, Sahiner, Berkman, Wei, Jun, Goodsitt, Mitchell M, Hadjiiski, Lubomir M, Jun, Ge, and Chuan, Zhou. A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis. United States: N. p., 2006.
Web. doi:10.1118/1.2237543.
Yiheng, Zhang, Chan, H -P, Sahiner, Berkman, Wei, Jun, Goodsitt, Mitchell M, Hadjiiski, Lubomir M, Jun, Ge, & Chuan, Zhou. A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis. United States. https://doi.org/10.1118/1.2237543
Yiheng, Zhang, Chan, H -P, Sahiner, Berkman, Wei, Jun, Goodsitt, Mitchell M, Hadjiiski, Lubomir M, Jun, Ge, and Chuan, Zhou. Sun .
"A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis". United States. https://doi.org/10.1118/1.2237543.
@article{osti_20853597,
title = {A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis},
author = {Yiheng, Zhang and Chan, H -P and Sahiner, Berkman and Wei, Jun and Goodsitt, Mitchell M and Hadjiiski, Lubomir M and Jun, Ge and Chuan, Zhou},
abstractNote = {Digital tomosynthesis mammography (DTM) is a promising new modality for breast cancer detection. In DTM, projection-view images are acquired at a limited number of angles over a limited angular range and the imaged volume is reconstructed from the two-dimensional projections, thus providing three-dimensional structural information of the breast tissue. In this work, we investigated three representative reconstruction methods for this limited-angle cone-beam tomographic problem, including the backprojection (BP) method, the simultaneous algebraic reconstruction technique (SART) and the maximum likelihood method with the convex algorithm (ML-convex). The SART and ML-convex methods were both initialized with BP results to achieve efficient reconstruction. A second generation GE prototype tomosynthesis mammography system with a stationary digital detector was used for image acquisition. Projection-view images were acquired from 21 angles in 3 deg. increments over a {+-}30 deg. angular range. We used an American College of Radiology phantom and designed three additional phantoms to evaluate the image quality and reconstruction artifacts. In addition to visual comparison of the reconstructed images of different phantom sets, we employed the contrast-to-noise ratio (CNR), a line profile of features, an artifact spread function (ASF), a relative noise power spectrum (NPS), and a line object spread function (LOSF) to quantitatively evaluate the reconstruction results. It was found that for the phantoms with homogeneous background, the BP method resulted in less noisy tomosynthesized images and higher CNR values for masses than the SART and ML-convex methods. However, the two iterative methods provided greater contrast enhancement for both masses and calcification, sharper LOSF, and reduced interplane blurring and artifacts with better ASF behaviors for masses. For a contrast-detail phantom with heterogeneous tissue-mimicking background, the BP method had strong blurring artifacts along the x-ray source motion direction that obscured the contrast-detail objects, while the other two methods can remove the superimposed breast structures and significantly improve object conspicuity. With a properly selected relaxation parameter, the SART method with one iteration can provide tomosynthesized images comparable to those obtained from the ML-convex method with seven iterations, when BP results were used as initialization for both methods.},
doi = {10.1118/1.2237543},
url = {https://www.osti.gov/biblio/20853597},
journal = {Medical Physics},
issn = {0094-2405},
number = 10,
volume = 33,
place = {United States},
year = {2006},
month = {10}
}
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