An efficient content-based medical image retrieval based on a new Canny steerable texture filter and Brownian motion weighted deep learning neural network

Author:

Rao R. VaraprasadaORCID,Prasad T. Jaya Chandra

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software

Reference49 articles.

1. Sezavar, A., Farsi, H., Mohamadzadeh, S.: Content-based image retrieval by combining convolutional neural networks and sparse representation. Multimedia Tools Appl. 78(6), 1–18 (2019)

2. Agarwal, M., Singhal, A., Lall, B.: Multi-channel local ternary pattern for content-based image retrieval. Pattern Anal. Appl. 22(8), 1–12 (2019)

3. Hussain, C.A., Rao, D.V., Mastani, A.S.: RetrieveNet a novel deep network for medical image retrieval. Evol. Intel. (2020). https://doi.org/10.1007/s12065-020-00401-z

4. Ashraf, R., Ahmed, M., Ahmad, U., AsifHabib, M., Jabbar, S., Naseer, K.: MDCBIR-MF multimedia data for content-based image retrieval by using multiple features. Multimed Tools Appl. (2018). https://doi.org/10.1007/s11042-018-5961-1

5. Biji, K.R., Marikkannu, P.: An efficient content based image retrieval using an optimized neural network for medical application. Multimedia Tools Appl. 79(19), 1–16 (2020)

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