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Medical Imaging
Why does endoscopic imaging require powerful computing performance?
High-quality endoscopic video requires multiple real-time image processing steps including bad pixel correction, noise reduction, color restoration and distortion correction. For 4K endoscopic video at 30/60fps, massive pixel data needs to be calculated every second. In addition, modern endoscopy systems demand 3D reconstruction, lesion segmentation and AI analysis. Meanwhile, three core challenges must be addressed: low latency for real-time operation, adaptive image optimization under complex lighting inside cavities, and concurrent running of AI detection models. Traditional single-processor architecture cannot handle these heavy tasks, making heterogeneous multi-core computing essential for smart endoscopic imaging.
Medical AI
Why does endoscopic imaging require powerful computing performance?
High-quality endoscopic video requires multiple real-time image processing steps including bad pixel correction, noise reduction, color restoration and distortion correction. For 4K endoscopic video at 30/60fps, massive pixel data needs to be calculated every second. In addition, modern endoscopy systems demand 3D reconstruction, lesion segmentation and AI analysis. Meanwhile, three core challenges must be addressed: low latency for real-time operation, adaptive image optimization under complex lighting inside cavities, and concurrent running of AI detection models. Traditional single-processor architecture cannot handle these heavy tasks, making heterogeneous multi-core computing essential for smart endoscopic imaging.
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