EMBC'11 Paper Abstract

Close

Paper SaP24.30

Enlow, Matthew (Pacific Northwest National Laboratory), Ju, Tao (Washington University in St. Louis), Kakadiaris, Ioannis (University of Houston), Carson, James (Pacific Northwest National Laboratory)

Lossless 3-D Reconstruction and Registration of Semi-Quantitative Gene Expression Data in the Mouse Brain

Scheduled for presentation during the Poster Session "Image Processing: Filtering, Enhancement, Segmentation, Registration, Classification, Compression, and Coding" (SaP24), Saturday, September 3, 2011, 15:30−17:00, America Ballroom Westin

33rd Annual International IEEE EMBS Conference, August 30 - September 3, 2011, Boston Marriott Copley Place, Boston, MA, USA

This information is tentative and subject to change. Compiled on October 21, 2019

Keywords Deformable image registration, Brain Image Analysis, Rigid-body image registration

Abstract

As imaging, computing, and data storage technologies improve, there is an increasing opportunity for multiscale analysis of three-dimensional datasets (3-D). Such analysis enables, for example, microscale elements of multiple macroscale specimens to be compared throughout the entire macroscale specimen. Spatial comparisons require bringing datasets into co-alignment. One approach for co-alignment involves elastic deformations of data in addition to rigid alignments. The elastic deformations distort space, and if not accounted for, can distort the information at the microscale. The algorithms developed in this work address this issue by allowing multiple data points to be encoded into a single image pixel, appropriately tracking each data point to ensure lossless data mapping during elastic spatial deformation. This approach was developed and implemented for both 2-D and 3-D registration of images. Lossless reconstruction and registration was applied to semi-quantitative cellular gene expression data in the mouse brain, enabling comparison of multiple spatially registered 3-D datasets without any augmentation of the cellular data. Standard reconstruction and registration without the lossless approach resulted in errors in cellular quantities of ~ 8%.

 

 

Technical Content Copyright © IEEE Engineering in Medicine and Biology Society, All rights reserved.