The DOI matches its Crossref record; 176 of the 176 references it cites were found in a registry or an index.
Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms
Open accessAbstract
Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique’s performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided.
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Dermatologist-level classification of skin cancer with deep neural networks
Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017) · Nature · doi:10.1038/nature21056 · Cited by 14,362
Skin Lesion Classification Using Convolutional Neural Network With Novel Regularizer
Albahar, M. A. (2019) · IEEE Access · doi:10.1109/access.2019.2906241 · Cited by 293
A multi-class skin Cancer classification using deep convolutional neural networks
Chaturvedi, S. S., Tembhurne, J. V., & Diwan, T. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09388-2 · Cited by 283
A Mobile-Based Deep Learning Model for Cassava Disease Diagnosis
Ramcharan, A., McCloskey, P., Baranowski, K., Mbilinyi, N., Mrisho, L., Ndalahwa, M., Legg, J., & Hughes, D. P. (2019) · Frontiers in Plant Science · doi:10.3389/fpls.2019.00272 · Cited by 264
Skin disease diagnosis with deep learning: a review
Li, H., Pan, Y., Zhao, J., & Zhang, L. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.08.096 · Cited by 178
Metadata
- Authors
- Masood, A., & Ali Al-Jumaily, A.
- Venue
- International Journal of Biomedical Imaging
- Publisher
- Hindawi Limited
- Published
- 2013
- Volume
- 2013
- Pages
- 1-22
- ISSN
- 1687-4188 (ISSN-L)
- 1687-4196
- OpenAlex
- W1998451602
- Cited by
- 347
- References
- 176
- FWCI
- 6.01
- Type
- journal article
- Language
- en
- Open access
- gold
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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.
