[en] In this paper, we analyze image textures with help of anisotropic fractional Brownian fields. We also use some anisotropy indices characterizing the anisotropy of these textures. Multi-oriented quadratic variations form the basis of mentioned indices. Anisotropy indices are invariant to some image transforms. Furthermore they can be estimated from the observed data. An application of these indices, combining with a measure of texture roughness, is in lesion detection in mammograms.
Disciplines :
Human health sciences: Multidisciplinary, general & others
Author, co-author :
Moallemian, Soodeh ; Université de Liège - ULiège > GIGA > GIGA CRC In vivo Imaging - Aging & Memory
Najibi Morteza; Lund University > Department of Clinical Sciences, Lund Section III
Yari Gholam Hossein
Language :
English
Title :
Using Machine Learning to Estimate Some Anisotropy Indices, Application to Brownian Textures and Breast Images
Publication date :
03 September 2017
Event name :
Conference on Modern Methods in Insurance Pricing and Industrial Statistics (MIPIS 2017))
Event place :
Iran
Event date :
3-5 September 2017
By request :
Yes
Audience :
International
Main work title :
Using Machine Learning to Estimate Some Anisotropy Indices, Application to Brownian Textures and Breast Images
Publisher :
Conference on Modern methods insurance pricing an industrial statistics, Iran
