Author:
Yao Bingying,Chao Li,Asadi Mehdi,Alnowibet Khalid A.
Abstract
AbstractThe diagnosis of leukemia is a serious matter that requires immediate and accurate attention. This research presents a revolutionary method for diagnosing leukemia using a Capsule Neural Network (CapsNet) with an optimized design. CapsNet is a cutting-edge neural network that effectively captures complex features and spatial relationships within images. To improve the CapsNet's performance, a Modified Version of Osprey Optimization Algorithm (MOA) has been utilized. Thesuggested approach has been tested on the ALL-IDB database, a widely recognized dataset for leukemia image classification. Comparative analysis with various machine learning techniques, including Combined combine MobilenetV2 and ResNet18 (MBV2/Res) network, Depth-wise convolution model, a hybrid model that combines a genetic algorithm with ResNet-50V2 (ResNet/GA), and SVM/JAYA demonstrated the superiority of our method in different terms. As a result, the proposed method is a robust and powerful tool for diagnosing leukemia from medical images.
Publisher
Springer Science and Business Media LLC
Reference22 articles.
1. Anilkumar, K., Manoj, V. & Sagi, T. Automated detection of leukemia by pretrained deep neural networks and transfer learning: A comparison. Med. Eng. Phys. 98, 8–19 (2021).
2. Liu, Y. & Bao, Y. Automatic interpretation of strain distributions measured from distributed fiber optic sensors for crack monitoring. Measurement 211, 112629 (2023).
3. Luo, Z. Knowledge-guided aspect-based summarization. In 2023 International Conference on Communications, Computing and Artificial Intelligence (CCCAI) (ed. Luo, Z.) 17–22 (IEEE, 2023).
4. Rajinikanth, V., Razmjooy, N. & Ghadimi, N. Design of a system for melanoma diagnosis using image processing and hybrid optimization techniques. In Frontiers of Artificial Intelligence in Medical Imaging (eds Razmjooy, N. & Rajinikanth, V.) (IOP Publishing, 2022).
5. Das, P. K. & Meher, S. An efficient deep convolutional neural network based detection and classification of acute lymphoblastic leukemia. Expert Syst. Appl. 183, 115311 (2021).