title: Towards real-time image deconvolution: application to confocal and STED microscopy.
abstract: Although deconvolution can improve the quality of any type of microscope, the high computational time required has so far limited its massive spreading. Here we demonstrate the ability of the scaled-gradient-projection (SGP) method to provide accelerated versions of the most used algorithms in microscopy. To achieve further increases in efficiency, we also consider implementations on graphic processing units (GPUs). We test the proposed algorithms both on synthetic and real data of confocal and STED microscopy. Combining the SGP method with the GPU implementation we achieve a speed-up factor from about a factor 25 to 690 (with respect the conventional algorithm). The excellent results obtained on STED microscopy images demonstrate the synergy between super-resolution techniques and image-deconvolution. Further, the real-time processing allows conserving one of the most important property of STED microscopy, i.e the ability to provide fast sub-diffraction resolution recordings.
authors: Laboratorio delle Tecnologie per Terapie Avanzate, Università di Ferrara, Ferrara, Italy.
authors: R
authors: R
authors: Zanella
authors: G
authors: G
authors: Zanghirati
authors: R
authors: R
authors: Cavicchioli
authors: L
authors: L
authors: Zanni
authors: P
authors: P
authors: Boccacci
authors: M
authors: M
authors: Bertero
authors: G
authors: G
authors: Vicidomini
mesh_terms: D000465:Algorithms; D003196:Computer Graphics / Q000295:instrumentation*; D003199:Computer Systems; D004867:Equipment Design; D019544:Equipment Failure Analysis; D007089:Image Enhancement / Q000295:instrumentation* / Q000379:methods*; D018613:Microscopy, Confocal / Q000295:instrumentation* / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000295:instrumentation* / Q000379:methods*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation
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