Fibered fluorescence microscopy (FFM) of intra epidermal nerve fibers-translational marker for peripheral neuropathies in preclinical research: processing and analysis of the dataFibered fluorescence microscopy (FFM) of intra epidermal nerve fibers-translational marker for peripheral neuropathies in preclinical research: processing and analysis of the data
Faculty of Sciences. Physics
2008Bellingham :Spie-int soc optical engineering, 2008
Applications of digital image processing XXX
Conference on Applications of Digital Image Processing XXXI, Aug. 11-14, 2008, San Diego, Calif.
7073(2008), 16 p.
University of Antwerp
Peripheral neuropathy can be caused by diabetes or AIDS or be a side-effect of chemotherapy. Fibered Fluorescence Microscopy (FFM) is a recently developed imaging modality using a fiber optic probe connected to a laser scanning unit. It allows for in-vivo scanning of small animal subjects by moving the probe along the tissue surface. In preclinical research, FFM enables non-invasive, longitudinal in vivo assessment of intra epidermal nerve fibre density in various models for peripheral neuropathies. By moving the probe, FFM allows visualization of larger surfaces, since, during the movement, images are continuously captured, allowing to acquire an area larger then the field of view of the probe. For analysis purposes, we need to obtain a single static image from the multiple overlapping frames. We introduce a mosaicing procedure for this kind of video sequence. Construction of mosaic images with sub-pixel alignment is indispensable and must be integrated into a global consistent image aligning. An additional motivation for the mosaicing is the use of overlapping redundant information to improve the signal to noise ratio of the acquisition, because the individual frames tend to have both high noise levels and intensity inhomogeneities. For longitudinal analysis, mosaics captured at different times must be aligned as well. For alignment, global correlation-based matching is compared with interest point matching. Use of algorithms working on multiple CPU's (parallel processor/cluster/grid) is imperative for use in a screening model.