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Landmark Detection for Fusion of Fundus and MRI Toward a Patient-Specific Multimodal Eye Model

Authors :
Jens Kowal
Philippe Maeder
Francis L. Munier
Meritxell Bach Cuadra
Tobias Rudolph
Carlos Ciller
Aubin Balmer
Sandro De Zanet
Source :
De Zanet, Sandro; Ciller, Carlos; Rudolph, Tobias; Maeder, P.; Munier, F.; Balmer, A.; Bach Cuadra, M.; Kowal, Horst Jens (2014). Landmark Detection for Fusion of Fundus and MRI Towards a Patient-Specific Multi-Modal Eye Model. IEEE transactions on biomedical engineering, 62(2), pp. 532-540. Institute of Electrical and Electronics Engineers IEEE 10.1109/TBME.2014.2359676
Publisher :
Ieee-Inst Electrical Electronics Engineers Inc

Abstract

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise e.g., Fundus photography, Optical Coherence Tomography (OCT), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The presented article’s goal is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI which was not visible before like vessels and the macula. This article’s contributions include automatic detection of the optic disc, the fovea, the optic axis and an automatic segmentation of the vitreous humor of the eye.

Details

Database :
OpenAIRE
Journal :
De Zanet, Sandro; Ciller, Carlos; Rudolph, Tobias; Maeder, P.; Munier, F.; Balmer, A.; Bach Cuadra, M.; Kowal, Horst Jens (2014). Landmark Detection for Fusion of Fundus and MRI Towards a Patient-Specific Multi-Modal Eye Model. IEEE transactions on biomedical engineering, 62(2), pp. 532-540. Institute of Electrical and Electronics Engineers IEEE 10.1109/TBME.2014.2359676 <http://dx.doi.org/10.1109/TBME.2014.2359676>
Accession number :
edsair.doi.dedup.....83df9bce9130ab41055ec2d55f495ef8