Literature DB >> 25570069

Quantification of skull deformity for craniofacial research.

Irma Lam, Michael Cunningham, Craig Birgfeld, Matthew Speltz, Linda Shapiro.   

Abstract

Craniosynostosis, a disorder in which one or more fibrous joints of the skull fuse prematurely, causes skull malformation and may be associated with increased intracranial pressure and developmental delays. In order to perform medical research studies that relate phenotypic abnormalities to outcomes such as cognitive ability or results of surgery, biomedical researchers need an automated methodology for quantifying the degree of abnormality of the disorder. This paper addresses that need by proposing a set of features derived from CT scans of the skull that can be used for this purpose. A thorough set of experiments is used to evaluate the features as compared to two human craniofacial experts in a ranking evaluation.

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Mesh:

Year:  2014        PMID: 25570069      PMCID: PMC4288006          DOI: 10.1109/EMBC.2014.6943701

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


  4 in total

1.  Three-dimensional head shape quantification for infants with and without deformational plagiocephaly.

Authors:  I Atmosukarto; L G Shapiro; J R Starr; C L Heike; B Collett; M L Cunningham; M L Speltz
Journal:  Cleft Palate Craniofac J       Date:  2010-07

2.  Classifying Craniosynostosis with a 3D Projection-Based Feature Extraction System.

Authors:  Irma Lam; Michael Cunningham; Matthew Speltz; Linda Shapiro
Journal:  Proc IEEE Int Symp Comput Based Med Syst       Date:  2014-05

Review 3.  Management of craniosynostosis.

Authors:  Jayesh Panchal; Venus Uttchin
Journal:  Plast Reconstr Surg       Date:  2003-05       Impact factor: 4.730

Review 4.  Cranial sutures: a brief review.

Authors:  Bethany J Slater; Kelly A Lenton; Matthew D Kwan; Deepak M Gupta; Derrick C Wan; Michael T Longaker
Journal:  Plast Reconstr Surg       Date:  2008-04       Impact factor: 4.730

  4 in total
  2 in total

1.  Objective classification system for sagittal craniosynostosis based on suture segmentation.

Authors:  Xiaohua Qian; Hua Tan; Jian Zhang; Xiahai Zhuang; Leslie Branch; Chaire Sanger; Allison Thompson; Weiling Zhao; King Chuen Li; Lisa David; Xiaobo Zhou
Journal:  Med Phys       Date:  2015-09       Impact factor: 4.071

2.  Automated Sagittal Craniosynostosis Classification from CT Images Using Transfer Learning.

Authors:  Lei You; Guangming Zhang; Weiling Zhao; Matthew Greives R; Lisa David; Xiaobo Zhou
Journal:  Clin Surg       Date:  2020-02-27
  2 in total

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