The DOI matches its Crossref record; 107 of the 107 references it cites were found in a registry or an index.
Approaches for automated detection and classification of masses in mammograms
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Citations
Cites
A Computational Approach to Edge Detection
Canny, J. (1986) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1986.4767851 · Cited by 30,004
Textural Features for Image Classification
Haralick, R. M., Shanmugam, K., & Dinstein, I. (1973) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1973.4309314 · Cited by 22,886
(2012) · Encyclopedia of the Sciences of Learning · doi:10.1007/978-1-4419-1428-6_5195 · Cited by 19,370
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.
Geman, S., & Geman, D. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767596 · Cited by 17,949
Statistical pattern recognition: a review
Jain, A. K., Duin, P. W., & Mao, J. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.824819 · Cited by 6,767
Chiang, L. H., Russell, E. L., & Braatz, R. D. (2001) · Advanced Textbooks in Control and Signal Processing · doi:10.1007/978-1-4471-0347-9_3 · Cited by 5,003
On the Statistical Analysis of Dirty Pictures
Besag, J. (1986) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1986.tb01412.x · Cited by 4,191
Characterization of signals from multiscale edges
Mallat, S., & Zhong, S. (1992) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.142909 · Cited by 3,200
Pattern Recognition Principles
(2009) · Classification Methods for Remotely Sensed Data, Second Edition · doi:10.1201/9781420090741.ch2 · Cited by 3,188
Introduction to Bayesian Networks
(2019) · Operational Risk Modelling in Financial Services · doi:10.1002/9781119508557.ch12 · Cited by 2,569
Cited by
Dheeba, J., Albert Singh, N., & Tamil Selvi, S. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.01.010 · Cited by 380
Breast Cancer Detection and Diagnosis Using Mammographic Data: Systematic Review
Gardezi, S. J. S., Elazab, A., Lei, B., & Wang, T. (2019) · Journal of Medical Internet Research · doi:10.2196/14464 · Cited by 268
Yun, J., Oh, J., & Yun, I. (2020) · Applied Sciences · doi:10.3390/app10134519 · Cited by 7
Metadata
- Authors
- Cheng, H. D., Shi, X. J., Min, R., Hu, L. M., Cai, X. P., & Du, H. N.
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2006-04
- Volume
- 39
- Issue
- 4
- Pages
- 646-668
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W2109597745
- Cited by
- 538
- References
- 107
- FWCI
- 8.24
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Approaches for automated detection and classification of masses in mammograms. https://app.cochat.ai/papers/10.1016/j.patcog.2005.07.006
- The paper
- Cheng, H. D., Shi, X. J., Min, R., Hu, L. M., Cai, X. P., & Du, H. N. (2006). Approaches for automated detection and classification of masses in mammograms. Pattern Recognition. https://doi.org/10.1016/j.patcog.2005.07.006
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.
