A novel white blood cells segmentation algorithm based on adaptive neutrosophic similarity score.

A I ShahinAmira S AshourK M AminAmr A Sharawi

Published in: Health information science and systems (2017)

In this paper, a method based on adaptive neutrosphic sets similarity score is proposed in order to detect WBCs from a blood smear microscopic image and segment its components (nucleus and the cytoplasm). The proposed segmentation algorithm can be utilized for fully-automated classification systems, such systems can be either for the healthy WBCs or even for non-healthy WBCs specially the leukemia cells.

Keyphrases

deep learning
machine learning
induced apoptosis
convolutional neural network
cell cycle arrest
acute myeloid leukemia
cell death
signaling pathway
high throughput
single cell
pi k akt