The DOI matches its Crossref record; 56 of the 58 references it cites were found in a registry or an index.
Deep learning based classification of focal liver lesions with contrast-enhanced ultrasound
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“Wu et al. [22] applied a three-layer DBN in timeintensity curves (TICs) extracted from contrast-enhanced US (CEUS) video sequences in order to classify malignant and benign focal liver lesions.They achieved a highest accuracy of 86.36%, thus outperforming conventional machine methods such as linear discriminant analysis (LDA), k-nearest neighbors (k-NN), SVM, and back propagation net (BPN).”
From Deep Learning in Medical Ultrasound Analysis: A Review (2019) · cites this paper as [22]
Citations
Cites
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Cited by
Sorted by citations
Deep Learning in Medical Ultrasound Analysis: A Review
Liu, S., Wang, Y., Yang, X., Lei, B., Liu, L., Li, S. X., Ni, D., & Wang, T. (2019) · Engineering · doi:10.1016/j.eng.2018.11.020 · Cited by 798
Murtaza, G., Shuib, L., Abdul Wahab, A. W., Mujtaba, G., Mujtaba, G., Nweke, H. F., Al-garadi, M. A., Zulfiqar, F., Raza, G., & Azmi, N. A. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09716-5 · Cited by 342
Akkus, Z., Cai, J. C., Boonrod, A., Zeinoddini, A., Weston, A. D., Philbrick, K. A., & Erickson, B. J. (2019) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2019.06.004 · Cited by 324
Machine learning for medical ultrasound: status, methods, and future opportunities
Brattain, L. J., Telfer, B. A., Dhyani, M., Grajo, J. R., & Samir, A. E. (2018) · Abdominal Radiology · doi:10.1007/s00261-018-1517-0 · Cited by 262
Das, A., Acharya, U. R., Panda, S. S., & Sabut, S. (2018) · Cognitive Systems Research · doi:10.1016/j.cogsys.2018.12.009 · Cited by 200
Metadata
- Authors
- Wu, K., Chen, X., & Ding, M.
- Affiliations
- Huazhong University of Science and Technology (CN)
- Corresponding author
- Ding, Mingyue
- Venue
- Optik
- Publisher
- Elsevier BV
- Published
- 2014-08
- Volume
- 125
- Issue
- 15
- Pages
- 4057-4063
- ISSN
- 0030-4026 (ISSN-L)
- OpenAlex
- W2084415465
- Cited by
- 139
- References
- 58
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 15 · 2023: 21 · 2022: 18 · 2021: 25 · 2020: 15 · 2019: 13 · 2018: 6 · 2017: 6 · 2016: 1 · 2015: 6
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Optik (publishedVersion)
- Funders
- National 973 Project (2011CB933103)
- National 12th-Five Year Research Program of China (2012BAI13B02)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- focal liver lesions, contrast-enhanced ultrasound, benign versus malignant liver lesions, time-intensity curve, sparse non-negative matrix factorization, liver perfusion, deep learning classification
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