The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Cone‐beam volume CT breast imaging: Feasibility study
Abstract
X‐ray projection mammography, using a film/screen combination, or digital techniques, has proven to be the most effective imaging modality currently available for early detection of breast cancer. However, the inherent superimposition of structures makes a small carcinoma (a few millimeters in size) difficult to detect when it is occult or in dense breasts, leading to a high false‐positive biopsy rate. Cone‐beam x‐ray‐projection‐based volume imaging using flat panel detectors (FPDs) may allow obtaining three‐dimensional breast images, resulting in more accurate diagnosis of structures and patterns of lesions while eliminating the hard compression of breasts. This article presents a novel cone‐beam volume computed tomographic breast imaging (CBVCTBI) technique based on the above techniques. Through a variety of computer simulations, the key issues of the system and imaging techniques were addressed, including the x‐ray imaging geometry and corresponding reconstruction algorithms, x‐ray characteristics of breast tissue and lesions, x‐ray setting techniques, the absorbed dose estimation, and the quantitative effect of x‐ray scattering on image quality. The preliminary simulation results support the proposed CVBCTBI modality for breast imaging in respect to its feasibility and practicability. The absorbed dose level is comparable to that of current mammography and will not be a prominent problem for this imaging technique. Compared to conventional mammography, the proposed imaging technique with isotropic spatial resolution will potentially provide significantly better low‐contrast detectability of breast tumors and more accurate location of breast lesions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Numerical recipes in C: the art of scientific computing
(1993) · Choice Reviews Online · doi:10.5860/choice.30-5638 · Cited by 17,933
Feldkamp, L. A., Davis, L. C., & Kress, J. W. (1984) · Journal of the Optical Society of America A · doi:10.1364/josaa.1.000612 · Cited by 6,319
An accurate method for computer‐generating tungsten anode x‐ray spectra from 30 to 140 kV
Boone, J. M., & Seibert, J. A. (1997) · Medical Physics · doi:10.1118/1.597953 · Cited by 706
Absorbed Radiation Dose in Mammography
Richard Hammerstein, G., Miller, D. W., White, D. R., Ellen Masterson, M., Woodard, H. Q., & Laughlin, J. S. (1979) · Radiology · doi:10.1148/130.2.485 · Cited by 549
X-ray characterisation of normal and neoplastic breast tissues
Johns, P. C., & Yaffe, M. J. (1987) · Physics in Medicine and Biology · doi:10.1088/0031-9155/32/6/002 · Cited by 533
Boone, J. M., Fewell, T. R., & Jennings, R. J. (1997) · Medical Physics · doi:10.1118/1.598100 · Cited by 452
A general cone-beam reconstruction algorithm
Wang, G., Lin, T.-H., Cheng, P., & Shinozaki, D. M. (1993) · IEEE Transactions on Medical Imaging · doi:10.1109/42.241876 · Cited by 333
Siewerdsen, J. H., & Jaffray, D. A. (2000) · Medical Physics · doi:10.1118/1.1286590 · Cited by 216
Zhao, W., & Rowlands, J. A. (1997) · Medical Physics · doi:10.1118/1.598097 · Cited by 208
Compton scatter effects in CT reconstructions
Glover, G. H. (1982) · Medical Physics · doi:10.1118/1.595197 · Cited by 167
Cited by
Sidky, E. Y., & Pan, X. (2008) · Physics in Medicine and Biology · doi:10.1088/0031-9155/53/17/021 · Cited by 1,995
Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review
Guo, R., Lu, G., Qin, B., & Fei, B. (2018) · Ultrasound in Medicine & Biology · doi:10.1016/j.ultrasmedbio.2017.09.012 · Cited by 542
Giger, M. L., Chan, H., & Boone, J. (2008) · Medical Physics · doi:10.1118/1.3013555 · Cited by 311
Siewerdsen, J. H., Daly, M. J., Bakhtiar, B., Moseley, D. J., Richard, S., Keller, H., & Jaffray, D. A. (2006) · Medical Physics · doi:10.1118/1.2148916 · Cited by 283
Metadata
- Authors
- Chen, B., & Ning, R.
- Venue
- Medical Physics
- Publisher
- Wiley
- Published
- 2002-04-16
- Volume
- 29
- Issue
- 5
- Pages
- 755-770
- ISSN
- 0094-2405 (ISSN-L)
- 2473-4209
- OpenAlex
- W1991951294
- Cited by
- 277
- References
- 17
- FWCI
- 9.13
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Cone‐beam volume CT breast imaging: Feasibility study. https://app.cochat.ai/papers/10.1118/1.1461843
- The paper
- Chen, B., & Ning, R. (2002). Cone‐beam volume CT breast imaging: Feasibility study. Medical Physics. https://doi.org/10.1118/1.1461843
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.