Glaucoma is the one of the two major causes of blindness, which can be diagnosed through measurement of neuro-retinal optic cup-to-disc ratio (CDR). Automatic calculation of optic cup boundary is challenging due to the interweavement of blood vessels with the surrounding tissues around the cup. A multimodality fusion approach for neuroretinal cup detection improves the accuracy of the boundary estimation. The algorithm's effectiveness is demonstrated on 71 manually segmented retina fundus images collected from Singapore Eye Research Institute. By comparing our automatic cup height measurement to ground truth, we found that our method accurately detected neuro-retinal cup height for 69 images, achieved 97.2% accuracy. The evaluation was based on a criterion that is more stringent than the clinically acceptable inter- or intra-observer variability. This further leads to a large clinical evaluation of the algorithm involving 15 thousand patients from Australia and Singapore.