Abnormality classification using convolutional neural network for echocardiographic images
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/s11042-023-17108-9.pdf
Reference20 articles.
1. Deperlioglu O, Kose U, Gupta D, Khanna A, Sangaiah AK (2020) Diagnosis of heart diseases by a secure internet of health things system based on auto encoder deep neural network. Comput Commun 01(162):31–50. https://doi.org/10.1016/j.comcom.2020.08.011
2. Ansari MA, Mehrotra R, Agrawal R (2020) Detection and classification of brain tumor in MRI images using wavelet transform and support vector machine. J Interdisc Math 1–12
3. Heena A, Biradar N Maroof NM (2022) Chapter 2 Machine learning based detection and classification of heart abnormalities. In: Proc International Conference on Image Processing and Capsule Networks (ICIPCN). Springer Science and Business Media LLC. https://doi.org/10.1007/978-3-030-84760-9_2
4. Heena A, Biradar N, Maroof NM, Vishwanath P (2022) Processing of echocardiographic images using segmentation, feature extraction and classification for detection of heart abnormality. Global Transit Proc 3(1):13–19. https://doi.org/10.1016/j.gltp.2022.04.003
5. Heena A, Biradar N, Maroof NM (2020) Design and implementation of fractional order integral filter for denoising of echocardiographic images. In: Proceedings of the 2nd International Conference on IoT, Social, Mobile, Analytics & Cloud in Computational Vision & Bio-Engineering (ISMAC-CVB 2020).Elsevier. https://doi.org/10.2139/ssrn.3735736
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