A computer-aided diagnosis system for HEp-2 fluorescence intensity classification

作者：

Highlights：

• We present a computer-aided diagnosis (CAD) system classifying HEp-2 fluorescence intensity.

• We introduce a method to compute the gold standard using labels given by physicians.

• The CAD is tested on a new wide dataset and on other two public datasets.

• We compare our results with those provided by state-of-the-art methods.

摘要

•We present a computer-aided diagnosis (CAD) system classifying HEp-2 fluorescence intensity.•We introduce a method to compute the gold standard using labels given by physicians.•The CAD is tested on a new wide dataset and on other two public datasets.•We compare our results with those provided by state-of-the-art methods.

论文关键词：Computer-aided diagnosis,Indirect immunofluorescence,HEp-2 samples,Deep learning,Invariant Scattering Convolutional Networks

论文评审过程：Received 19 February 2018, Revised 8 September 2018, Accepted 6 November 2018, Available online 28 November 2018, Version of Record 13 June 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2018.11.002