Literature DB >> 22256310

Automated spatial alignment of 3D torso images.

Arijit Bose1, Shishir K Shah, Gregory P Reece, Melissa A Crosby, Elisabeth K Beahm, Michelle C Fingeret, Mia K Markey, Fatima A Merchant.   

Abstract

This paper describes an algorithm for automated spatial alignment of three-dimensional (3D) surface images in order to achieve a pre-defined orientation. Surface images of the torso are acquired from breast cancer patients undergoing reconstructive surgery to facilitate objective evaluation of breast morphology pre-operatively (for treatment planning) and/or post-operatively (for outcome assessment). Based on the viewing angle of the multiple cameras used for stereophotography, the orientation of the acquired torso in the images may vary from the normal upright position. Consequently, when translating this data into a standard 3D framework for visualization and analysis, the co-ordinate geometry differs from the upright position making robust and standardized comparison of images impractical. Moreover, manual manipulation and navigation of images to the desired upright position is subject to user bias. Automating the process of alignment and orientation removes operator bias and permits robust and repeatable adjustment of surface images to a pre-defined or desired spatial geometry.

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Year:  2011        PMID: 22256310     DOI: 10.1109/IEMBS.2011.6092086

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  1 in total

1.  3D surface imaging of the human female torso in upright to supine positions.

Authors:  Gregory P Reece; Fatima Merchant; Johnny Andon; Hamed Khatam; K Ravi-Chandar; June Weston; Michelle C Fingeret; Chris Lane; Kelly Duncan; Mia K Markey
Journal:  Med Eng Phys       Date:  2015-02-18       Impact factor: 2.242

  1 in total

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