Group velocity dispersion (GVD) and pulse front distortion of ultrashort pulses are of critical importance in
efficient multiphoton excitation microscopy. Since measurement of the pulse front distortion due to a lens is not trivial we have developed an imaging interferometric cross-correlator which allows us to measure temporal delays and pulse-widths across the spatial profile of the beam. The instrument consists of a modified Michelson interferometer with a reference arm containing a voice-coil delay stage and an arm which contains the optics under test. The pulse replicas are recombined and incident on a 22×22 lenslet array. The beamlets are focused in a 0.5 mm thick BBO crystal (cut for Type I second harmonic generation), filtered to remove the IR component of the beam and imaged using a 500 fps camera. The GVD and pulse front distortion are extracted from the temporal stack of beamlet images to produce a low resolution spatio-temporal map.
In many clinical studies, including those of cancer, it is highly desirable to acquire images of whole tumour sections whilst retaining a microscopic resolution. A usual approach to this is to create a composite image by appropriately overlapping individual images acquired at high magnification under a microscope. A mosaic of these images can be accurately formed by applying image registration, overlap removal and blending techniques. We describe an optimised, automated, fast and reliable method for both image joining and blending. These algorithms can be applied to most types of light microscopy imaging. Examples from histology, from in vivo vascular imaging and from fluorescence applications are shown, both in 2D and 3D. The algorithms are robust to the varying image overlap of a manually moved stage, though examples of composite images acquired both with manually-driven and computer-controlled stages are presented. The overlap-removal algorithm is based on the cross-correlation method; this is used to determine and select the best correlation point between any new image and the previous composite image. A complementary image blending algorithm, based on a gradient method, is used to eliminate sharp intensity changes at the image joins, thus gradually blending one image onto the adjacent 'composite'. The details of the algorithm to overcome both intensity discrepancies and geometric misalignments between the stitched images will be presented and illustrated with several examples.