The DOI matches its Crossref record; 84 of the 84 references it cites were found in a registry or an index.
A survey on the magnetic resonance image denoising methods
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Citations
Cites
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892
Scale-space and edge detection using anisotropic diffusion
Perona, P., & Malik, J. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.56205 · Cited by 12,119
Statistical parametric maps in functional imaging: A general linear approach
Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J. ‐., Frith, C. D., & Frackowiak, R. S. J. (1994) · Human Brain Mapping · doi:10.1002/hbm.460020402 · Cited by 9,688
De-noising by soft-thresholding
Donoho, D. L. (1995) · IEEE Transactions on Information Theory · doi:10.1109/18.382009 · Cited by 9,619
Ideal spatial adaptation by wavelet shrinkage
Donoho, D. L., & Johnstone, I. M. (1994) · Biometrika · doi:10.1093/biomet/81.3.425 · Cited by 8,760
Voxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
Bilateral Filtering for Gray and Color Images
Tomasi, C., & Manduchi, R. (2002) · Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271) · doi:10.1109/iccv.1998.710815 · Cited by 8,177
SENSE: Sensitivity encoding for fast MRI
Pruessmann, K. P., Weiger, M., Scheidegger, M. B., & Boesiger, P. (1999) · Magnetic Resonance in Medicine · doi:10.1002/(sici)1522-2594(199911)42:5<952::aid-mrm16>3.0.co;2-s · Cited by 6,251
Generalized autocalibrating partially parallel acquisitions (GRAPPA)
Griswold, M. A., Jakob, P. M., Heidemann, R. M., Nittka, M., Jellus, V., Wang, J., Kiefer, B., & Haase, A. (2002) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10171 · Cited by 5,303
A Review of Image Denoising Algorithms, with a New One
Buades, A., Coll, B., & Morel, J. M. (2005) · Multiscale Modeling & Simulation · doi:10.1137/040616024 · Cited by 4,083
Cited by
Deep Multi-Scale 3D Convolutional Neural Network (CNN) for MRI Gliomas Brain Tumor Classification
Mzoughi, H., Njeh, I., Wali, A., Slima, M. B., BenHamida, A., Mhiri, C., & Mahfoudhe, K. B. (2020) · Journal of Digital Imaging · doi:10.1007/s10278-020-00347-9 · Cited by 361
A review on medical image denoising algorithms
Mohd Sagheer, S. V., & George, S. N. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102036 · Cited by 316
Metadata
- Authors
- Mohan, J., Krishnaveni, V., & Guo, Y.
- Venue
- Biomedical Signal Processing and Control
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 9
- Pages
- 56-69
- ISSN
- 1746-8094 (ISSN-L)
- OpenAlex
- W2046372571
- Cited by
- 295
- References
- 84
- FWCI
- 17.10
- Type
- journal article
- Language
- en
- Open access
- closed
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- Mohan, J., Krishnaveni, V., & Guo, Y. (2014). A survey on the magnetic resonance image denoising methods. Biomedical Signal Processing and Control. https://doi.org/10.1016/j.bspc.2013.10.007
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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.
