The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Texture Feature Analysis for Computer-Aided Diagnosis on Pulmonary Nodules
Open accessOverview
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
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
A comparative study of texture measures with classification based on featured distributions
Ojala, T., Pietikäinen, M., & Harwood, D. (1996) · Pattern Recognition · doi:10.1016/0031-3203(95)00067-4 · Cited by 6,882
Armato, S. G., McLennan, G., Bidaut, L., McNitt‐Gray, M. F., Meyer, C. R., Reeves, A. P., Zhao, B., Aberle, D. R., Henschke, C. I., Hoffman, E. A., et al. (2011) · Medical Physics · doi:10.1118/1.3528204 · Cited by 2,887
Jones, J. P., & Palmer, L. A. (1987) · Journal of Neurophysiology · doi:10.1152/jn.1987.58.6.1233 · Cited by 1,658
Cited by
Cancer Diagnosis Using Deep Learning: A Bibliographic Review
Munir, K., Elahi, H., Ayub, A., Frezza, F., & Rizzi, A. (2019) · Cancers · doi:10.3390/cancers11091235 · Cited by 422
Med3D: Transfer Learning for 3D Medical Image Analysis
Chen, S., Ma, K., & Zheng, Y. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.00625 · Cited by 317
Cervical cancer classification using convolutional neural networks and extreme learning machines
Ghoneim, A., Muhammad, G., & Hossain, M. S. (2020) · Future Generation Computer Systems · doi:10.1016/j.future.2019.09.015 · Cited by 312
Hussein, S., Kandel, P., Bolan, C. W., Wallace, M. B., & Bagci, U. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2894349 · Cited by 285
Xie, Y., Zhang, J., Xia, Y., Fulham, M., & Zhang, Y. (2018) · Information Fusion · doi:10.1016/j.inffus.2017.10.005 · Cited by 284
Metadata
- Authors
- Han, F., Wang, H., Zhang, G., Han, H., Song, B., Li, L., Moore, W., Lu, H., Zhao, H., & Liang, Z.
- Venue
- Journal of Digital Imaging
- Published
- 2014-08-13
- Volume
- 28
- Issue
- 1
- Pages
- 99-115
- ISSN
- 0897-1889 (ISSN-L)
- 1618-727X
- OpenAlex
- W2078014989
- Cited by
- 265
- References
- 4
- FWCI
- 8.90
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Texture Feature Analysis for Computer-Aided Diagnosis on Pulmonary Nodules. https://app.cochat.ai/papers/10.1007/s10278-014-9718-8
- The paper
- Han, F., Wang, H., Zhang, G., Han, H., Song, B., Li, L., Moore, W., Lu, H., Zhao, H., & Liang, Z. (2015). Texture Feature Analysis for Computer-Aided Diagnosis on Pulmonary Nodules. Journal of Digital Imaging. https://doi.org/10.1007/s10278-014-9718-8
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.
