Detail-preserving construction of neonatal brain atlases in space-frequency domain

Yuyao Zhang, Feng Shi, Pew Thian Yap, Dinggang Shen

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

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.

Original languageEnglish
JournalHuman Brain Mapping
DOIs
Publication statusAccepted/In press - 2016

Fingerprint

Atlases
Brain
Wavelet Analysis
Neuroimaging

Keywords

  • Brain atlas
  • Frequency decomposition
  • Image registration
  • MRI template
  • Neonatal brain
  • Neonate
  • Pediatrics
  • Sparse representation
  • Wavelet transform

ASJC Scopus subject areas

  • Clinical Neurology
  • Anatomy
  • Neurology
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Cite this

Detail-preserving construction of neonatal brain atlases in space-frequency domain. / Zhang, Yuyao; Shi, Feng; Yap, Pew Thian; Shen, Dinggang.

In: Human Brain Mapping, 2016.

Research output: Contribution to journalArticle

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