Accurate Recognition of Leukemia Sub-types by Utilizing a Transfer Learned Deep Convolutional Neural Network
- 5 April 2021
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 427-430
Abstract
Leukemia has been causing more than 350,000 deaths per year despite holding a notable number of studies on the prognosis, diagnosis, and therapy for Leukemia. Computerized Leukemia disclosure may change the circumstances, as steps can be obtained instantly, hence, precise identification of Leukemia has been a domain of concern for researchers for nearly a decade now. Lately, many contributions have been bestowed to the scientific society concerning the identification of Leukemia. But with the expansion and development of the datasets, the demand for accurate identification of Leukemia is becoming more demanding every day. In this research, we examined a Leukemia sub-types dataset that consists of three kinds of Leukemia individuals. We introduced and implemented a modified DenseNet-201 design and produced an overall accuracy of 99.56% which exceeded all the previous investigations.Keywords
This publication has 22 references indexed in Scilit:
- SnapShot: Acute Myeloid LeukemiaCancer Cell, 2012
- Automatic Classification of Lymphoma Images With Transform-Based Global FeaturesIEEE Transactions on Information Technology in Biomedicine, 2010
- The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changesBlood, 2009
- WND-CHARM: Multi-purpose image classification using compound image transformsPattern Recognition Letters, 2008
- Texture classification using nonlinear color quantization: Application to histopathological image analysisInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2008
- Classification of hematologic malignancies using texton signaturesPattern Analysis and Applications, 2007
- Low Dimensional Adaptive Texture Feature Vectors From Class Distance and Class Difference MatricesIEEE Transactions on Medical Imaging, 2004
- When and How to Treat Chronic Lymphocytic LeukemiaNew England Journal of Medicine, 2000
- Supervised and Unsupervised Discretization of Continuous Features1995
- Childhood LeukemiaNew England Journal of Medicine, 1969