Open AccessDetail‐preserving construction of neonatal brain atlases in space‐frequency domain
Author(s) -
Zhang Yuyao,
Shi Feng,
Yap PewThian,
Shen Dinggang
Publication year - 2016
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.23160
Subject(s) - atlas (anatomy) , computer science , artificial intelligence , brain atlas , neuroimaging , population , frequency domain , computer vision , pattern recognition (psychology) , neuroscience , biology , anatomy , demography , sociology
Brain atlases are commonly utilized in neuroimaging studies. However, most brain atlases are fuzzy and lack structural details, especially in the cortical regions. This is mainly caused by the image averaging process involved in atlas construction, which often smoothes out high‐frequency contents that capture fine anatomical details. Brain atlas construction for neonatal images is even more challenging due to insufficient spatial resolution and low tissue contrast. In this paper, we propose a novel framework for detail‐preserving construction of population‐representative atlases. Our approach combines spatial and frequency information to better preserve image details. This is achieved by performing atlas construction in the space‐frequency domain given by wavelet transform. In particular, sparse patch‐based atlas construction is performed in all frequency subbands, and the results are combined to give a final atlas. For enhancing anatomical details, tissue probability maps are also used to guide atlas construction. Experimental results show that our approach can produce atlases with greater structural details than existing atlases. Hum Brain Mapp 37:2133–2150, 2016 . © 2016 Wiley Periodicals, Inc.