计算机科学
显微镜
显微镜
镜头(地质)
数字化病理学
分辨率(逻辑)
照相机镜头
人工智能
计算机视觉
降低成本
视野
微透镜
摄影
光学
计算机图形学(图像)
物理
艺术
管理
经济
视觉艺术
作者
Tomas Aidukas,Regina Eckert,Andrew R. Harvey,Laura Waller,Pavan Chandra Konda
标识
DOI:10.1038/s41598-019-43845-9
摘要
Abstract The revolution in low-cost consumer photography and computation provides fertile opportunity for a disruptive reduction in the cost of biomedical imaging. Conventional approaches to low-cost microscopy are fundamentally restricted, however, to modest field of view (FOV) and/or resolution. We report a low-cost microscopy technique, implemented with a Raspberry Pi single-board computer and color camera combined with Fourier ptychography (FP), to computationally construct 25-megapixel images with sub-micron resolution. New image-construction techniques were developed to enable the use of the low-cost Bayer color sensor, to compensate for the highly aberrated re-used camera lens and to compensate for misalignments associated with the 3D-printed microscope structure. This high ratio of performance to cost is of particular interest to high-throughput microscopy applications, ranging from drug discovery and digital pathology to health screening in low-income countries. 3D models and assembly instructions of our microscope are made available for open source use.
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