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Journal article

HEp-2 Cell Classification Using Shape Index Histograms With Donut-Shaped Spatial Pooling

From

Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Office of the President, Administration, Technical University of Denmark3

We present a new method for automatic classification of indirect immunoflourescence images of HEp-2 cells into different staining pattern classes. Our method is based on a new texture measure called shape index histograms that captures second-order image structure at multiple scales. Moreover, we introduce a spatial decomposition scheme which is radially symmetric and suitable for cell images.

The spatial decomposition is performed using donut-shaped pooling regions of varying sizes when gathering histogram contributions. We evaluate our method using both the ICIP 2013 and the ICPR 2012 competition datasets. Our results show that shape index histograms are superior to other popular texture descriptors for HEp-2 cell classification.

Moreover, when comparing to other automated systems for HEp-2 cell classification we show that shape index histograms are very competitive; especially considering the relatively low complexity of the method.

Language: English
Publisher: IEEE
Year: 2014
Pages: 1573-1580
ISSN: 1558254x and 02780062
Types: Journal article
DOI: 10.1109/TMI.2014.2318434
ORCIDs: Larsen, Rasmus and 0000-0002-1718-1755

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