We demonstrate a new fluorescent imaging technique that can screen for fluorescent micro-objects over an ultra-wide field-of-view (FOV) of ~532 cm2, i.e., 19 cm × 28 cm, reaching a space-bandwidth product of more than 2 billion. For achieving such a large FOV, we modified the hardware and software of a commercially available flatbed scanner, and added a custom-designed absorbing fluorescent filter, a two-dimensional array of external light sources for computer-controlled and high-angle fluorescent excitation. We also re-programmed the driver of the scanner to take full control of the scanner hardware and achieve the highest possible exposure time, gain and sensitivity for detection of fluorescent micro-objects through the gradient index self-focusing lens array that is positioned in front of the scanner sensor chip. For example, this large FOV of our imaging platform allows us to screen more than 2.2 mL of undiluted whole blood for detection of fluorescent micro-objects within <5 minutes. This high-throughput fluorescent imaging platform could be useful for rare cell research and cytometry applications by enabling rapid screening of large volumes of optically dense media. Our results constitute the first time that a flatbed scanner has been converted to a fluorescent imaging system, achieving a record large FOV.
Abstract. Images rendered with traditional computer graphics techniques, such as scanline rendering and ray tracing, appear focused at all depths. However, there are advantages to having blur, such as adding realism to a scene or drawing attention to a particular place in a scene. In this paper we describe the optics underlying camera models that have been used in computer graphics, and present object space techniques for rendering with those models. In our companion paper [3], we survey image space techniques to simulate these models. These techniques vary in both speed and accuracy.
Abstract. Images rendered with traditional computer graphics techniques, such as scanline rendering and ray tracing, appear focused at all depths. However, there are advantages to having blur, such as adding realism to a scene or drawing attention to a particular place in a scene. In this paper we describe the optics underlying camera models that have been used in computer graphics, and present object space techniques for rendering with those models. In our companion paper [3], we survey image space techniques to simulate these models. These techniques vary in both speed and accuracy.
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