Multimodal multidimensional imaging for visual system status assessment

Non-invasive optical methods that enable in vivo or in situ visualization of tissue components are of particular relevance in ophthalmology, as they can provide key information about the relationship between the structure and function of the visual system. In this paper we present a semiautomated multimodal imaging tool for co-registration of images of retinal structure and its function, based on point correspondence. Decision support analysis was applied to define significant features for the multimodal mapping system, using a set of 1500 subjects who were affected by blindness associated hereditary retinal dystrophies. Additionally, the developed software was tested by two experienced observers using data from 25 subjects. Inter-observer and intra-observer reliability was determined. We conclude that semi-automated multimodal mapping could be a promising new tool for an individualized visual system status assessment that can be applied for the early diagnosis of blindness associated diseases. Moreover, this mapping approach should prove particularly appropriate for studying pathophysiology in inherited blindness associated diseases.