The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Automatic recognition of five types of white blood cells in peripheral blood
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Cites
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
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
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A Tutorial on Support Vector Machines for Pattern Recognition
Burges, C. J. C. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009715923555 · Cited by 16,429
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
Ojala, T., Pietikainen, M., & Maenpaa, T. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017623 · Cited by 15,398
Artificial neural networks: fundamentals, computing, design, and application
Basheer, I. A., & Hajmeer, M. (2000) · Journal of Microbiological Methods · doi:10.1016/s0167-7012(00)00201-3 · Cited by 3,231
Floating search methods in feature selection
Pudil, P., Novovičová, J., & Kittler, J. (1994) · Pattern Recognition Letters · doi:10.1016/0167-8655(94)90127-9 · Cited by 3,098
Texture classification using the support vector machines
Li, S., Kwok, J. T., Zhu, H., & Wang, Y. (2003) · Pattern Recognition · doi:10.1016/s0031-3203(03)00219-x · Cited by 198
Morphological feature extraction for the classification of digital images of cancerous tissues
Thiran, J.-P., & Macq, B. (1996) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.536902 · Cited by 167
A texture approach to leukocyte recognition
Sabino, D. M. U., Costa, L. D. F., Rizzatti, E. G., & Zago, M. A. (2004) · Real-Time Imaging · doi:10.1016/j.rti.2004.02.007 · Cited by 153
Cited by
Chen, Y., Zhang, C., Chen, B., Huang, Y., Sun, Y., Wang, C., Fu, X., Dai, Y., Qin, F., Peng, Y., et al. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.107917 · Cited by 423
Classification of acute lymphoblastic leukemia using deep learning
Rehman, A., Abbas, N., Saba, T., Rahman, S. I. U., Mehmood, Z., & Kolivand, H. (2018) · Microscopy Research and Technique · doi:10.1002/jemt.23139 · Cited by 328
An efficient multi-level convolutional neural network approach for white blood cells classification
Cheuque, C., Querales, M., León, R., Salas, R., & Torres, R. (2022) · Diagnostics · doi:10.3390/diagnostics12020248 · Cited by 116
Combining support vector machine with genetic algorithm to classify ultrasound breast tumor images
Wu, W.-J., Lin, S.-W., & Moon, W. K. (2012) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2012.07.004 · Cited by 99
Metadata
- Authors
- Rezatofighi, S. H., & Soltanian-Zadeh, H.
- Venue
- Computerized Medical Imaging and Graphics
- Publisher
- Elsevier BV
- Published
- 2011-06
- Volume
- 35
- Issue
- 4
- Pages
- 333-343
- ISSN
- 0730-4862 (ISSN-L)
- 0895-6111
- OpenAlex
- W1980276039
- Cited by
- 411
- References
- 16
- FWCI
- 4.83
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Rezatofighi, S. H., & Soltanian-Zadeh, H. (2011). Automatic recognition of five types of white blood cells in peripheral blood. Computerized Medical Imaging and Graphics. https://doi.org/10.1016/j.compmedimag.2011.01.003
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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.
