Robust head CT image registration pipeline for craniosynostosis skull correction surgery
- Author(s): Shusil Dangi 1 ; Hina Shah 2 ; Antonio R. Porras 3 ; Beatriz Paniagua 2 ; Cristian A. Linte 1, 4 ; Marius Linguraru 3, 5 ; Andinet Enquobahrie 2
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View affiliations
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Affiliations:
1:
Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology , Rochester, NY , USA ;
2: Kitware Inc. , Carrboro, NC , USA ;
3: Sheikh Zayed Institute for Pediatric Surgical Innovation , Children's National Health System , Washington, DC , USA ;
4: Biomedical Engineering , Rochester Institute of Technology , Rochester, NY , USA ;
5: School of Medicine and Health Sciences , George Washington University , Washington, DC , USA
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Affiliations:
1:
Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology , Rochester, NY , USA ;
- Source:
Volume 4, Issue 5,
October
2017,
p.
174 – 178
DOI: 10.1049/htl.2017.0067 , Online ISSN 2053-3713
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Inspec keywords: biomechanics; surgery; computerised tomography; medical image processing; optimisation; deformation; image resolution; bone; image registration
Other keywords: initial optimisation; deformation; congenital malformation; template skull; corrective surgery; presurgical computed tomography image; craniosynostosis skull correction surgery; patient-specific skull model extraction; infant skull; targeted skull region; robust multistage multiresolution registration pipeline; optimal correction strategy; normal CT images; mean surface-to-surface distance; robust head CT image registration pipeline; very low resolution; patient-specihc CT image
Subjects: Patient diagnostic methods and instrumentation; X-ray techniques: radiography and computed tomography (biomedical imaging/measurement); Patient care and treatment; Optical, image and video signal processing; Mechanical properties of tissues and organs; Optimisation techniques; Computer vision and image processing techniques; Optimisation techniques; Patient care and treatment; Biology and medical computing; X-rays and particle beams (medical uses)
References
-
-
1)
-
1. Lajeunie, E., Merrer, M.L., Binaiti-Pellie, C., et al: ‘Genetic study of nonsyndromic coronal craniosynostosis’, Am. J. Med. Genet., 1995, 55, (4), pp. 500–504 (doi: 10.1002/ajmg.1320550422).
-
-
2)
-
2. Nagaraja, S., Anslow, P., Winter, B.: ‘Craniosynostosis’, Clin. Radiol., 2013, 68, (3), pp. 284–292 (doi: 10.1016/j.crad.2012.07.005).
-
-
3)
-
3. Kirmi, O., Lo, S.J., Johnson, D., et al: ‘Craniosynostosis: a radiological and surgical perspective’, In: Seminars in Ultrasound, CT and MRI, 2009, vol. 30, Elsevier, pp. 492–512.
-
-
4)
-
4. Szpalski, C., Weichman, K., Sagebin, F., et al: ‘Need for standard outcome reporting systems in craniosynostosis’, Neurosurgical Focus, 2011, 31, (2), pp. E1 (doi: 10.3171/2011.6.FOCUS1192).
-
-
5)
-
5. Mendoza, C.S., Safdar, N., Okada, K., et al: ‘Personalized assessment of craniosynostosis via statistical shape modeling’, Med. Image Anal., 2014, 18, (4), pp. 635–646 (doi: 10.1016/j.media.2014.02.008).
-
-
6)
-
6. Maintz, J.A., Viergever, M.A.: ‘A survey of medical image registration’, Med. Image Anal., 1998, 2, (1), pp. 1–36 (doi: 10.1016/S1361-8415(01)80026-8).
-
-
7)
-
7. Viergever, M.A., Maintz, J.A., Klein, S., et al: ‘A survey of medical image registration - under review’, Med. Image Anal., 2017, 33, pp. 140–144 (doi: 10.1016/j.media.2016.06.030).
-
-
8)
-
8. Saber, N.R., Phillips, J., Looi, T., et al: ‘Generation of normative pediatric skull models for use in cranial vault remodeling procedures’, Child’s Nervous Syst., 2012, 28, (3), pp. 405–410 (doi: 10.1007/s00381-011-1630-7).
-
-
9)
-
13. Myronenko, A., Song, X.: ‘Point set registration: coherent point drift’, IEEE Trans. Pattern Anal. Mach. Intell., 2010, 32, (12), pp. 2262–2275 (doi: 10.1109/TPAMI.2010.46).
-
-
10)
-
10. Sahillioglu, Y., Kavan, L.: ‘Skuller: a volumetric shape registration algorithm for modeling skull deformities’, Med. Image Anal., 2015, 23, (1), pp. 15–27 (doi: 10.1016/j.media.2015.03.005).
-
-
11)
-
11. Porras, A.R., Zukic, D., Equobahrie, A., et al: ‘Personalized optimal planning for the surgical correction of metopic craniosynostosis’. In: Workshop on Clinical Image-Based Procedures, 2016, Springer, pp. 60–67.
-
-
12)
-
12. Goldman, L.W.: ‘Principles of CT and CT technology’, J. Nucl. Med. Technol., 2007, 35, (3), pp. 115–128 (doi: 10.2967/jnmt.107.042978).
-
-
13)
-
13. Avants, B.B., Tustison, N.J., Stauffer, M., et al: ‘The insight toolkit image registration framework’, Front. Neuroinform., 2014, 8, pp. 44 (doi: 10.3389/fninf.2014.00044).
-
-
1)
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