Iterative randomized irregular circular algorithm for proliferation rate estimation in brain tumor Ki-67 histology images
作者：
Highlights：
• This CAD system calculates proliferation rate estimation (PRE) automatically.
• A novel Iterative Randomized Irregular Circular Algorithm (IRIC) has been proposed.
• The Brain Tumor Ki-67 Histology Images are taken from UKM Medical Centre.
• Prior to a random set region of interest, IRIC counts blue and brown cells and PRE.
• IRIC outperforms Circular Hough Transform about 98% and of F-measurement rate.
摘要
•This CAD system calculates proliferation rate estimation (PRE) automatically.•A novel Iterative Randomized Irregular Circular Algorithm (IRIC) has been proposed.•The Brain Tumor Ki-67 Histology Images are taken from UKM Medical Centre.•Prior to a random set region of interest, IRIC counts blue and brown cells and PRE.•IRIC outperforms Circular Hough Transform about 98% and of F-measurement rate.
论文关键词：Circle detection,Ki-67,Nuclei counting,Proliferation rate,Digital histopathology,Brain tumor
论文评审过程：Received 12 August 2014, Revised 18 November 2015, Accepted 19 November 2015, Available online 2 December 2015, Version of Record 23 December 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.11.012
