3D volume reconstruction of a mouse brain from histological sections using warp filtering

Tao Ju, Joe Warren, James Carson, Musodiq Bello, Ioannis Kakadiaris, Wah Chiu, Christina Thaller, Gregor Eichele

Research output: Contribution to journalArticlepeer-review

81 Scopus citations


Sectioning tissues for optical microscopy often introduces upon the resulting sections distortions that make 3D reconstruction difficult. Here we present an automatic method for producing a smooth 3D volume from distorted 2D sections in the absence of any undistorted references. The method is based on pairwise elastic image warps between successive tissue sections, which can be computed by 2D image registration. Using a Gaussian filter, an average warp is computed for each section from the pairwise warps in a group of its neighboring sections. The average warps deform each section to match its neighboring sections, thus creating a smooth volume where corresponding features on successive sections lie close to each other. The proposed method can be used with any existing 2D image registration method for 3D reconstruction. In particular, we present a novel image warping algorithm based on dynamic programming that extends Dynamic Time Warping in 1D speech recognition to compute pairwise warps between high-resolution 2D images. The warping algorithm efficiently computes a restricted class of 2D local deformations that are characteristic between successive tissue sections. Finally, a validation framework is proposed and applied to evaluate the quality of reconstruction using both real sections and a synthetic volume.

Original languageEnglish (US)
Pages (from-to)84-100
Number of pages17
JournalJournal of Neuroscience Methods
Issue number1-2
StatePublished - Sep 30 2006


  • 3D reconstruction
  • Dynamic programming
  • Filtering
  • Histology
  • Image warping

ASJC Scopus subject areas

  • Neuroscience(all)


Dive into the research topics of '3D volume reconstruction of a mouse brain from histological sections using warp filtering'. Together they form a unique fingerprint.

Cite this