Curvelet based contrast enhancement in fluoroscopic sequences
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The document discusses a novel method for enhancing contrast in fluoroscopic sequences while minimizing radiation exposure. It introduces a curvelet-based denoising technique that involves a recursive temporal filter and spatial filtering to preserve low-contrast structures, followed by a line enhancement step to improve visibility. Evaluations indicate that this approach can achieve a 50% reduction in dose while enhancing feature detection.
Curvelet based contrast enhancement in fluoroscopic sequences
- 1. CURVELET BASED CONTRAST ENHANCEMENT IN FLUOROSCOPIC SEQUENCES ABSTRACT Image guided interventions have seen growing interestin recent years. The use of X-rays for the procedure impelslimiting the dose over time. Image sequences obtained thereby exhibit high levels of noise and very low contrasts. Hence, thedevelopment of efficient methods to enable optimal visualizationof these sequences is crucial. We propose an original denoising method based on the curve let transform. First, we apply a recursivetemporal filter to the curvelet coefficients. As some residualnoise remains, a spatial filtering is performed in the second step,which uses a magnitude-based classification and a contextualcomparison of curvelet coefficients. This procedure allows to denoise the sequence while preserving low-contrasted structures,but does not improve their contrast. Finally, a third step is carriedout to enhance the features of interest. For this, we propose aline enhancement technique in the curvelet domain. Indeed, thinstructures are sparsely represented in that domain, allowing a fastand efficient detection. Quantitative and qualitative evaluationsperformed on synthetic and real low-dose sequences demonstratethat the proposed method enables a 50% dose reduction.