Geodesic Geometric Mean of Regional Covariance Descriptors as an Image-Level Descriptor for Nuclear Atypia Grading in Breast Histology Images

Abstract

The region covariance descriptors have recently become a popular method for detection and tracking of objects in an image. However, these descriptors are not suitable for classification of images with heterogeneous contents. In this paper, we present an image-level descriptor obtained using an affine-invariant geodesic mean of region covariance descriptors… (More)
DOI: 10.1007/978-3-319-10581-9_13

Topics

5 Figures and Tables

Statistics

050100201520162017
Citations per Year

Citation Velocity: 10

Averaging 10 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.

Cite this paper

@inproceedings{Khan2014GeodesicGM, title={Geodesic Geometric Mean of Regional Covariance Descriptors as an Image-Level Descriptor for Nuclear Atypia Grading in Breast Histology Images}, author={Adnan Mujahid Khan and Korsuk Sirinukunwattana and Nasir M. Rajpoot}, booktitle={MLMI}, year={2014} }