An efficient CAD system for ALL cell identification from microscopic blood images

Author:

Mohammed Zhana Fidakar,Abdulla Alan AnwerORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference24 articles.

1. Alexandra B, Pavel K, Jan Z (2020) Automated detection of acute lymphoblastic leukemia from microscopic images based on human visual perception. J Front Bioeng Biotechnol 8:1005

2. Anto Bennet M, Diana G, Pooja U, Ramya N (2019) Texture Metric Driven Acute Lymphoid Leukemia Classification Using Artificial Neural Network. Int J Recent Technol Eng (IJRTE) 7(6S3):152–156

3. Bhabatosh et al. (2011) Digital image processing and analysis. PHI Learning

4. Bhargavi K, Jyothi S (2014) A survey on threshold based segmentation technique in image processing. Int J Innov Res Develop 3(12):234–239

5. ElDahshan KA, Youssef MI, Masameer EH, Mustafa MA (2015) An efficient implementation of acute lymphoblastic leukemia images segmentation on the FPGA. Adv Image Vid Process 3(3):8–17

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