April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Fusion of fundus images and MRI data of the human eye
Author Affiliations & Notes
  • Sandro Ivo De Zanet
    Ophthalmic Technology, ARTORG Center for Biomedical Engineering Research, Bern, Switzerland
    Ophthalmology, Inselspital Bern, Bern, Switzerland
  • Carlos Ciller
    Ophthalmic Technology, ARTORG Center for Biomedical Engineering Research, Bern, Switzerland
    Department of Radiology, CHUV/MIAL, Universite de Lausanne, Lausanne, Switzerland
  • Philippe Maeder
    Department of Radiology, CHUV/MIAL, Universite de Lausanne, Lausanne, Switzerland
  • Francis L Munier
    Unit of Pediatric Ocular Oncology, Jules Goning Eye Hospital, Lausanne, Switzerland
  • Jens Horst Kowal
    Ophthalmic Technology, ARTORG Center for Biomedical Engineering Research, Bern, Switzerland
    Ophthalmology, Inselspital Bern, Bern, Switzerland
  • Footnotes
    Commercial Relationships Sandro De Zanet, None; Carlos Ciller, None; Philippe Maeder, None; Francis Munier, None; Jens Kowal, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 5846. doi:
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    • Get Citation

      Sandro Ivo De Zanet, Carlos Ciller, Philippe Maeder, Francis L Munier, Jens Horst Kowal; Fusion of fundus images and MRI data of the human eye. Invest. Ophthalmol. Vis. Sci. 2014;55(13):5846.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

Ophthalmologists are confronted with a set of different image modalities to diagnose eye tumors e.g., fundus photography, CT and MRI. However, these images are often complementary and represent pathologies differently. Some aspects of tumors can only be seen in a particular modality. A fusion of modalities would improve the contextual information for diagnosis. The presented work attempts to register color fundus photography with MRI volumes. This would complement the low resolution 3D information in the MRI with high resolution 2D fundus images.

 
Methods
 

MRI volumes were acquired from 12 infants under the age of 5 with unilateral retinoblastoma. The contrast-enhanced T1-FLAIR sequence was performed with an isotropic resolution of less than 0.5mm. Fundus images were acquired with a RetCam camera. For healthy eyes, two landmarks were used: the optic disk and the fovea. The eyes were detected and extracted from the MRI volume using a 3D adaption of the Fast Radial Symmetry Transform (FRST). The cropped volume was automatically segmented using the Split Bregman algorithm. The optic nerve was enhanced by a Frangi vessel filter. By intersection the nerve with the retina the optic disk was found. The fovea position was estimated by constraining the position with the angle between the optic and the visual axis as well as the distance from the optic disk. The optical axis was detected automatically by fitting a parable on to the lens surface. On the fundus, the optic disk and the fovea were detected by using the method of Budai et al. Finally, the image was projected on to the segmented surface using the lens position as the camera center. In tumor affected eyes, the manually segmented tumors were used instead of the optic disk and macula for the registration.

 
Results
 

In all of the 12 MRI volumes that were tested the 24 eyes were found correctly, including healthy and pathological cases. In healthy eyes the optic nerve head was found in all of the tested eyes with an error of 1.08 +/- 0.37mm. A successful registration can be seen in figure 1.

 
Conclusions
 

The presented method is a step toward automatic fusion of modalities in ophthalmology. The combination enhances the MRI volume with higher resolution from the color fundus on the retina. Tumor treatment planning is improved by avoiding critical structures and disease progression monitoring is made easier.

 
 
Three stages of reconstruction: Point cloud, Surface, Registration
 
Three stages of reconstruction: Point cloud, Surface, Registration
 
Keywords: 549 image processing • 550 imaging/image analysis: clinical • 688 retina  
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