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Deep Transfer Learning with Fused Optimal Features for Detection of Diabetic Foot Ulcers

by Venkatesan Rajinikanth 1,*
1
Department of Computer Science and Engineering, Division of Research and Innovation, Saveetha School of Engineering, SIMATS, Chennai 602105, TN, India.
*
Author to whom correspondence should be addressed.
IJCMR  2023, 14; 1(3), 14; https://doi.org/10.61466/ijcmr1030014
Received: 8 October 2023 / Accepted: 9 November 2023 / Published Online: 10 November 2023

Abstract

Abstract:

Background:

As a result of the availability of high-speed computing devices, disease screening procedures in modern hospitals have significantly improved over the last few decades. As a result of this invention of deep learning procedures (DP), this work implemented modern diagnostic schemes to achieve accurate and fast results when screening patients for diseases with the aid of medical data.

Method:

This study applied pre-trained DP to detect Diabetic Foot Ulcers (DFU) from the test images. This work consists following stages; (i) Resizing, augmenting, and enhancing images, (ii) deep-features mining with a chosen DP, (iii) features reduction using 50% dropout and serial features-fusion, and (iv) Binary-classification through five-fold cross-validation. Two types of disease detection procedures implemented during the investigation: (a) Conventional deep-features and (b) fused deep-features (FD).

Result:

As a result of this study, the FD obtained with VGG16 and ResNet101 enabled 99.5% accuracy in DFU detection using SoftMax classifier.

Conclusion:

This demonstration confirmed that the proposed scheme is effective in detecting DFU from the chosen database.


Copyright: © 2023 by Rajinikanth. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Rajinikanth, V. Deep Transfer Learning with Fused Optimal Features for Detection of Diabetic Foot Ulcers. International Journal of Clinical Medical Research, 2023, 1, 14. https://doi.org/10.61466/ijcmr1030014
AMA Style
Rajinikanth V. Deep Transfer Learning with Fused Optimal Features for Detection of Diabetic Foot Ulcers. International Journal of Clinical Medical Research; 2023, 1(3):14. https://doi.org/10.61466/ijcmr1030014
Chicago/Turabian Style
Rajinikanth, Venkatesan 2023. "Deep Transfer Learning with Fused Optimal Features for Detection of Diabetic Foot Ulcers" International Journal of Clinical Medical Research 1, no.3:14. https://doi.org/10.61466/ijcmr1030014

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