Anatomically Correct Surface Recovery: A Statistical Approach

Rasmus Ramsbøl Jensen, Jannik Boll Nielsen, Rasmus Larsen, Rasmus Reinhold Paulsen

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We present a method for 3D surface recovery in partial surface scans. The method is based on an Active Shape Model, which is used to predict missing data. The model is constructed using a bootstrap framework, where an initially small collection of hand-annotated samples is used to fit to and register unknown samples, resulting in an extensive statistical model. The statistical recovery uses a multivariate point prediction, where the distribution of the points is given by the Active Shape Model. We show how missing data in a partial scan, once point correspondence is achieved, can be predicted using the learned statistics. A quantitative evaluation is performed on a data set of 10 laser scans of ear canal impressions with minimal noise and artificial holes. We also present a qualitative evaluation on authentic partial scans from an actual direct in ear scanner prototype. Compared to a state-of-the-art surface reconstruction algorithm, the presented method gives matching prediction results for the synthetic evaluation samples and superior results for the direct scanner data.
Original languageEnglish
Title of host publicationImage Analysis : 19th Scandinavian Conference, SCIA 2015 Copenhagen, Denmark, June 15–17, 2015 Proceedings
Number of pages12
PublisherSpringer Science+Business Media
Publication date2015
ISBN (Print)978-3-319-19664-0
ISBN (Electronic)978-3-319-19665-7
Publication statusPublished - 2015
Event19th Scandinavian Conference on Image Analysis - Copenhagen, Denmark
Duration: 15 Jun 201517 Jun 2015
Conference number: 19


Conference19th Scandinavian Conference on Image Analysis
Internet address
SeriesLecture Notes in Computer Science


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