An efficient deep Convolutional Neural Network based detection and classification of Acute Lymphoblastic Leukemia

作者：

Highlights：

• A novel deep CNNs-based Acute Lymphoblastic Leukemia (ALL) classification.

• A novel probability-based weight factor (Wf) is proposed.

• It hybridizes MobilenetV2 and ResNet18 with preserving both methods’ benefits.

• Moreover, the hybrid method is faster and efficient than the ensemble approach.

摘要

•A novel deep CNNs-based Acute Lymphoblastic Leukemia (ALL) classification.•A novel probability-based weight factor (Wf) is proposed.•It hybridizes MobilenetV2 and ResNet18 with preserving both methods’ benefits.•Moreover, the hybrid method is faster and efficient than the ensemble approach.

论文关键词：Acute Lymphoblastic Leukemia,Classification,Deep learning,Hematological disorder,Transfer learning

论文评审过程：Received 19 January 2021, Revised 16 April 2021, Accepted 30 May 2021, Available online 8 June 2021, Version of Record 25 June 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115311