Groupwise diffeomorphic non-rigid registration for automatic model building

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We describe a framework for registering a group of images together using a set of non-linear diffeomorphic warps. The result of the groupwise registration is an implicit definition of dense correspondences between all of the images in a set, which can be used to construct statistical models of shape change across the set, avoiding the need for manual annotation of training images. We give examples on two datasets (brains and faces) and show the resulting models of shape and appearance variation. We show results of experiments demonstrating that the groupwise approach gives a more reliable correspondence than pairwise matching alone. © Springer-Verlag Berlin Heidelberg 2004.

Bibliographical metadata

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.
PublisherSpringer Nature
Pages316-327
Number of pages11
Volume3024
Publication statusPublished - 2004
EventEuropean Conference on Computer Vision - Copenhagen
Event duration: 1 Jan 1824 → …

Publication series

NameLecture Notes in Computer Science
PublisherSpinger

Conference

ConferenceEuropean Conference on Computer Vision
CityCopenhagen
Period1/01/24 → …