Multi-atlas multi-shape segmentation of fetal brain MRI for volumetric and morphometric analysis of ventriculomegaly

NeuroImage

Volumn 60, Issue 3, 2012, Pages 1819-1831

  Gholipour, Ali ^a   Akhondi Asl, Alireza ^a   Estroff, Judy A ^a   Warfield, Simon K ^a  

^a BOSTON CHILDREN S HOSPITAL   (United States)

Author keywords

Automatic segmentation; Fetal MRI; Super resolution volume reconstruction; Ventriculomegaly

Indexed keywords

BIOLOGICAL MARKER;

ANATOMICAL VARIATION; ARTICLE; BRAIN DEVELOPMENT; BRAIN VENTRICLE DILATATION; CLINICAL ARTICLE; CONTROLLED STUDY; FETUS; FETUS (ANATOMY); FETUS BRAIN; FETUS ECHOGRAPHY; GESTATIONAL AGE; HUMAN; IMAGING AND DISPLAY; LATERAL BRAIN VENTRICLE; MORPHOMETRICS; MULTI ATLAS MULTI SHAPE SEGMENTATION; NERVOUS SYSTEM PARAMETERS; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; VENTRICULAR ATRIAL DIAMETER; VOLUMETRY;

ALGORITHMS; COMPUTER SIMULATION; HUMANS; HYDROCEPHALUS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MODELS, ANATOMIC; PATTERN RECOGNITION, AUTOMATED; PRENATAL DIAGNOSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84857751333     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2012.01.128     Document Type: Article

References (66)

1. Akhondi-Asl A., Jafari-Khouzani K., Elisevich K., Soltanian-Zadeh H. Hippocampal volumetry for lateralization of temporal lobe epilepsy: Automated versus manual methods. NeuroImage 2011, 54(Supplement 1):S218-S226.
2. Akhondi-Asl A., Soltanian-Zadeh H. Effect of number of coupled structures on the segmentation of brain structures. J. Signal Process. Syst. 2009, 54(1):215-230.
3. Akhondi-Asl A., Soltanian-Zadeh H. Two-stage multishape segmentation of brain structures using image intensity, tissue type, and location information. Med. Phys. 2010, 37:4501.
4. Akhondi-Asl A., Warfield S. Cortical brain structures segmentation using constrained optimization and intensity coupling. Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on. IEEE 2011, 2022-2025.
5. Aljabar P., Heckemann R., Hammers A., Hajnal J., Rueckert D. Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy. NeuroImage 2009, 46(3):726-738.
6. Artaechevarria X., Munoz-Barrutia A. Combination strategies in multi-atlas image segmentation: application to brain MR data. IEEE Trans. Med. Imaging 2009, 28(8):1266-1277.
7. Asman A., Landman B. Characterizing spatially varying performance to improve multi-atlas multi-label segmentation. Information Processing in Medical Imaging 2011, 85-96. Springer, New York.
8. Avants B., Epstein C., Grossman M., Gee J. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 2008, 12(1):26.
9. Beeghly M., Ware J., Soul J., Du Plessis A., Khwaja O., Senapati G., Robson C., Robertson R., Poussaint T., Barnewolt C., et al. Neurodevelopmental outcome of fetuses referred for ventriculomegaly. Ultrasound Obstet. Gynecol. 2010, 35(4):405-416.
10. Cardoza J.D., Goldstein R.B., Filly R.A. Exclusion of fetal ventriculomegaly with a single measurement: the width of the lateral ventricular atrium. Radiology 1988, 169(3):711-714.
11. Chan T., Vese L. Active contours without edges. IEEE Trans. Image Process. 2001, 10(2):266-277.
12. Clouchoux C., Kudelski D., Gholipour A., Warfield S., Viseur S., Bouyssi-Kobar M., Mari J.-L., Evans A., du Plessis A., Limperopoulos C. Quantitative in vivo MRI measurement of cortical development in the fetus. Brain Struct. Funct. 2011, 1-13.
13. Commowick O., Warfield S. A continuous STAPLE for scalar, vector, and tensor images: an application to DTI analysis. IEEE Trans. Med. Imaging 2009, 28(6):838-846.
14. Commowick O., Warfield S. Incorporating priors on expert performance parameters for segmentation validation and label fusion: a maximum a posteriori STAPLE. Med. Image Comput. Comput. Assist. Interv. 2010, 25-32. 2010.
15. Gaglioti P., Danelon D., Bontempo S., Mombr M., Cardaropoli S., Todros T. Fetal cerebral ventriculomegaly: outcome in 176 cases. Ultrasound Obstet. Gynecol. 2005, 25:372-377.
16. Gaglioti P., Oberto M., Todros T. The significance of fetal ventriculomegaly: etiology, short- and long-term outcomes. Prenat. Diagn. 2009, 29:381-388.
17. Garel C. Imaging the fetus: when does MRI really help?. Pediatr. Radiol. 2008, 38:467-470.
18. Garel C., Luton D., Oury J.-F., Gressens P. Ventricular dilatations. Childs Nerv. Syst. 2003, 19:517-523.
19. Gerig G., Styner M., Jones D., Weinberger D., Lieberman J. Shape analysis of brain ventricles using SPHARM. Mathematical Methods in Biomedical Image Analysis, 2001. MMBIA 2001. IEEE Workshop on 2001, 171-178.
20. Gholipour A., Warfield S.K. Super-resolution reconstruction of fetal brain MRI. MICCAI Workshop on Image Analysis for the Developing Brain (IADB'2009) 2009, 24 Sept., URL http://www.crl.med.harvard.edu/publications/SR-Fetal-Brain-MRI-IADB-MICCAI2009.pdf. C. Studholme, F. Rousseau (Eds.).
21. Gholipour A., Kehtarnavaz N., Briggs R., Devous M., Gopinath K. Brain functional localization: a survey of image registration techniques. IEEE Trans. Med. Imaging 2007, 26(4):427-451.
22. Gholipour A., Estroff J., Warfield S. Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans. Med. Imaging 2010, 29(10):1739-1758. Oct.
23. Gholipour A., Estroff J., Barnewolt C., Connolly S., Warfield S. Fetal brain volumetry through MRI volumetric reconstruction and segmentation. Int. J. Comput. Assist. Radiol. Surg. 2011, 6:329-339.
24. Glenn O. MR imaging of the fetal brain. Pediatr. Radiol. 2010, 40(1):68-81.
25. Goshtasby A. 2-D and 3-D Image Registration 2005, Wiley-Interscience, New York.
26. Grossman R., Hoffman C., Mardor Y., Biegon A. Quantitative MRI measurements of human fetal brain development in utero. NeuroImage 2006, 33(2):463-470.
27. Guibaud L. Fetal cerebral ventricular measurement and ventriculomegaly: time for procedure standardization. Ultrasound Obstet. Gynecol. 2009, 34:127-130.
28. Habas P., Kim K., Corbett-Detig J., Rousseau F., Glenn O., Barkovich A., Studholme C. A spatiotemporal atlas of MR intensity, tissue probability and shape of the fetal brain with application to segmentation. NeuroImage 2010, 53(2):460-470.
29. Habas P., Kim K., Rousseau F., Glenn O., Barkovich A., Studholme C. Atlas-based segmentation of developing tissues in the human brain with quantitative validation in young fetuses. Hum. Brain Mapp. 2010, 31(9):1348-1358.
30. Heckemann R., Hajnal J., Aljabar P., Rueckert D., Hammers A. Automatic anatomical brain MRI segmentation combining label propagation and decision fusion. NeuroImage 2006, 33(1):115-126.
31. Isgum I., Staring M., Rutten A., Prokop M., Viergever M., van Ginneken B. Multi-atlas-based segmentation with local decision fusion-application to cardiac and aortic segmentation in CT scans. IEEE Trans. Med. Imaging 2009, 28(7):1000-1010.
32. Jacob F., Habas P., Kim K., Corbett-Detig J., Xu D., Studholme C., Glenn O. Fetal hippocampal development: analysis by magnetic resonance imaging volumetry. Pediatr. Res. 2011, 69(5 Part 1):425.
33. Jiang S., Xue H., Glover A., Rutherford M., Rueckert D., Hajnal J. MRI of moving subjects using multislice snapshot images with volume reconstruction (SVR): application to fetal, neonatal, and adult brain studies. IEEE Trans. Med. Imaging July 2007, 26(7):967-980.
34. Kazan-Tannus J.F., Dialani V., Kataoka M.L., Chiang G., Feldman H.A., Brown J.S., Levine D. MR volumetry of brain and csf in fetuses referred for ventriculomegaly. Am. J. Roentgenol. 2007, 189(1):145-151.
35. Kelly E., Allen V., Seaward G., Windrim R., Ryan G. Mild ventriculomegaly in the fetus, natural history, associated findings and outcome of isolated mild ventriculomegaly: a literature review. Prenat. Diagn. 2001, 21:697-700.
36. Kennelly M., Cooley S., McParland P. Natural history of apparently isolated severe fetal ventriculomegaly: perinatal survival and neurodevelopmental outcome. Prenat. Diagn. 2009, 29:1135-1140.
37. Kim K., Habas P., Rousseau F., Glenn O., Barkovich A., Studholme C. Intersection based motion correction of multi-slice MRI for 3D in utero fetal brain image formation. IEEE Trans. Med. Imaging Jan. 2010, 29(1):146-158.
38. Klein S., van der Heide U., Lips I., van Vulpen M., Staring M., Pluim J. Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information. Med. Phys. 2008, 35:1407.
39. Levine D., Trop I., Mehta T.S., Barnes P.D. MR imaging appearance of fetal cerebral ventricular morphology. Radiology 2002, 223(3):652-660.
40. Levine D., Feldman H.A., Kazan Tannus J.F., Estroff J.A., Magnino M., Robson C.D., Poussaint T.Y., Barnewolt C.E., Mehta T.S., Robertson R.L. Frequency and cause of disagreements in diagnoses for fetuses referred for ventriculomegaly. Radiology 2008, 247(2):516-527.
41. Limperopoulos C., Clouchoux C. Advancing fetal brain MRI: targets for the future. Seminars in Perinatology 2009, vol. 33:289-298. Elsevier,
42. Lotjonen J., Wolz R., Koikkalainen J., Thurfjell L., Waldemar G., Soininen H., Rueckert D. Fast and robust multi-atlas segmentation of brain magnetic resonance images. NeuroImage 2010, 49(3):2352-2365.
43. Malladi R., Sethian J., Vemuri B. Shape modeling with front propagation: a level set approach. IEEE Trans. Pattern Anal. Mach. Intell. 1995, 17(2):158-175.
44. Mangin J. Entropy minimization for automatic correction of intensity nonuniformity. Proceedings. IEEE Workshop on. IEEE 2002, 162-169.
45. Mattes D., Haynor D., Vesselle H., Lewellen T., Eubank W. PET-CT image registration in the chest using free-form deformations. IEEE Trans. Med. Imaging 2003, 22(1):120-128.
46. Melchiorre K., Bhide A., Gika A., Pilu G., Papageorghiou A. Counseling in isolated mild fetal ventriculomegaly. Ultrasound Obstet. Gynecol. 2009, 34:212-224.
47. Melchiorre K., Liberati M., Celentano C., Domizio S., Puglielli C., Buoni S., Strambi M., Zannolli R. Neurological outcome following isolated 10-12 mm fetal ventriculomegaly. Arch. Dis. Child. Fetal Neonatal Ed. 2009, 94:311-312.
48. Osher S., Fedkiw R. Level Set Methods and Dynamic Implicit Surfaces 2003, vol. 153. Springer Verlag.
49. Pham D., Xu C., Prince J. Current methods in medical image segmentation. Annu. Rev. Biomed. Eng. 2000, 2(1):315-337.
50. Rohlfing T., Russakoff D., Maurer C. Expectation maximization strategies for multi-atlas multi-label segmentation. Information Processing in Medical Imaging 2003, 210-221. Springer, New York.
51. Rohlfing T., Brandt R., Menzel R., Maurer C., et al. Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains. NeuroImage 2004, 21(4):1428-1442.
52. Rousseau F., Glenn O.A., Iordanova B., Rodriguez-Carranza C., Vigneron D.B., Barkovich J.A., Studholme C. Registration-based approach for reconstruction of high-resolution in utero fetal MR brain images. Acad. Radiol. 2006, 13(9):1072-1081.
53. Rutherford M., Jiang S., Allsop J., Perkins L., Srinivasan L., Hayat T., Kumar S., Hajnal J. MR imaging methods for assessing fetal brain development. Dev. Neurobiol. 2008, 68(6):700-711.
54. Sabuncu M., Yeo B., Van Leemput K., Fischl B., Golland P. A generative model for image segmentation based on label fusion. IEEE Trans. Med. Imaging 2010, 29(10):1714-1729.
55. Sethian J. Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science 1999, 3. Cambridge Univ. Press, Cambridge.
56. Studholme C. Fetal MR imaging. Annu. Rev. Biomed. Eng. 2011, 13(1).
57. Styner M., Lieberman J.A., McClure R.K., Weinberger D.R., Jones D.W., Gerig G. Morphometric analysis of lateral ventricles in schizophrenia and healthy controls regarding genetic and disease-specific factors. Proc. Natl. Acad. Sci. U. S. A. 2005, 102(13):4872-4877.
58. Styner M., Oguz I., Xu S., Brechbühler C., Pantazis D., Levitt J., Shenton M., Gerig G. Framework for the statistical shape analysis of brain structures using SPHARM-PDM 2006, URL. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3062073/.
59. Thevenaz P., Unser M. Optimization of mutual information for multiresolution image registration. IEEE Trans. Image Process. 2002, 9(12):2083-2099.
60. Tsai A., Wells W., Tempany C., Grimson E., Willsky A. Mutual information in coupled multi-shape model for medical image segmentation. Med. Image Anal. 2004, 8(4):429-445.
61. van der Lijn F., den Heijer T., Breteler M., Niessen W. Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts. NeuroImage 2008, 43(4):708-720.
62. van Rikxoort E., Isgum I., Arzhaeva Y., Staring M., Klein S., Viergever M., Pluim J., van Ginneken B. Adaptive local multi-atlas segmentation: application to the heart and the caudate nucleus. Med. Image Anal. 2010, 14(1):39-49.
63. Warfield S., Zou K., Wells W. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Trans. Med. Imaging 2004, 23(7):903-921.
64. Weisenfeld N., Warfield S. Learning likelihoods for labeling (L3): a general multi-classifier segmentation algorithm. Med. Image Comput. Comput. Assist. Interv. 2011, 322-329.
65. Whitaker R. A level-set approach to 3D reconstruction from range data. Int. J. Comput. Vis. 1998, 29(3):203-231.
66. Xu C., Pham D., Prince J. Image segmentation using deformable models. Handbook of Medical Imaging. Med. Image Process. Anal. 2004, 2:129-174.