A new intelligent system for diagnosing tumors with MR images using type-2 fuzzy neural network (T2FNN)
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-021-11221-3.pdf
Reference55 articles.
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2. Ahmmed R, Rahman MA, Hossain MF (2018) Fuzzy logic based algorithm to classify tumor categories with position from brain MRI images. In: 3rd Int. Conf. Electr. Inf. Commun. Technol. EICT 2017, vol. 2018-Janua, no. December, pp 1–6. https://doi.org/10.1109/EICT.2017.8275232.
3. Al-Badarneh A, Alrazqi A, Najadat H (2015) Performance impact of texture features on MRI image classification. In: ACM Int. Conf. Proceeding Ser., vol. 24–26-Sept. https://doi.org/10.1145/2832987.2833063
4. Behzadfar N, Soltanian-Zadeh H (2012) Automatic segmentation of brain tumors in magnetic resonance images. In: Proc. - IEEE-EMBS Int. Conf. Biomed. Heal. Informatics Glob. Gd. Chall. Heal. Informatics, BHI 2012, vol 21, pp. 329–332. https://doi.org/10.1109/BHI.2012.6211580.
5. Benson CC, Lajish VL, Rajamani K (2017) Robust classification of MR brain images based on fractal dimension analysis. In: 2017 Int. Conf. Adv. Comput. Commun. Informatics, ICACCI 2017, pp 1135–1140 https://doi.org/10.1109/ICACCI.2017.8125994.
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