Department of Computer Science and Engineering
University of Washington

Shape-Based Retrieval of 3D Craniofacial Data

This research is supported by the National Institute of Dental and Craniofacial Research under Grant No. 1U01DE020050-01.

Click here for subproject Ontology of Craniofacial Development and Deformation .

Project Summary:

The goal of this work is to provide tools for the study of craniofacial anatomy from either CT scans or from a 12-camera active stereo photogrammetry system. Our image-analysis tools provide low-level operators for working with 3D craniofacial data. Our feature extraction tools produce quantitative representations (descriptors) of the 3D data that can be used to summarize the 3D shape as pertains to the condition being studied and the question being asked. Our similarity-measure tools compare the data from two individuals (or between an individual and the average of a population) and produce a numeric similarity score. Our organizational tools provide an image indexing mechanism that allows rapid retrieval of all images in a database that are similar to a query image in order of similarity. Our user-interface tools allow users to easily pose queries specifying both relational constraints on alphanumeric data and similarity constraints on image data in order to find subjects in a database who are most similar to a query subject with respect to studies from multiple different imaging modalities.

We will apply our tools for analysis, description, similarity measurement, organization and shape-based retrieval to a database of patients with midface hypoplasia and cleft lip and/or palate as part of the NIH/NIDCR FaceBase Consortium.

People:

Linda Shapiro, PI
James Brinkley, Key Personnel
Michael Cunningham, Key Personnel
Ezgi Mercan, CSE Fellow
Michael Lam, Research Programmer
Brinkley
Irma Lam, NLM Trainee
Jia Wu, RA
Lynn Yang, RA
Sara Rolfe, RA
Ambar Choudhury, Research Programmer





Collaborators:

Carrie Heike
Timothy Cox
Indriyati Atmosukarto
Katarzyna Wilamowska





Publications:


  • S. M. Rolfe, L. G. Shapiro, T. C. Cox, A.M. Maga, L. L. Cox, "A Landmark-free Framework for the Detection and Description of Shape Differences in Embryos", International IEEE EMBS Conference, 2011.

  • J. Wu, R. Tse, C. L. Heike, L. G. Shapiro, "Learning to Compute the Summetry Plane for Human Faces", ACM-BCB '11, August 2011.

  • S. Yang, L. G. Shapiro, M. L. Cunningham, M. Speltz, S.- I. Lee, "Classification and Feature Selection for Craniosynostosis," ACM-BCB '11, August 2011.

  • J. H. Chen and L. G. Shapiro, "Groupwise Pose Normalization for Craniofacial Applications," IEEE Workshop on Applications of Computer Vision, January 2011.

  • J.H. Chen, K. Zheng, and L. G. Shapiro, "3D Point Correspondence by Minimum Description Length in Feature Space," European Conference on Computer Vision, 2010.

  • I. Atmosukarto, L. G. Shapiro, C. Heike, "Use of Genetic Programming for Learning 3D Craniofacial Shape Quantification", ICPR 2010.
  • L Shapiro, K Wilamowska, I Atmosukarto, J Wu, CL Heike, M Spelz, and M Cunningham. "Shape-Based Classification of 3D Head Data." International Conference on Image Analysis and Processing, 2009.
  • Software

  • Software Manual for Processing of 3D CranioFacial Data
  • Progress Reports

  • 2011
  • 2010