研究目的
To design and test a 3D-printed focussing mechanism for a ball lens-based microscope to improve focus control for cellular microscopy in low-resource and educational settings.
研究成果
The 3D-printed focussing mechanism demonstrated micrometre-scale accuracy in maintaining focus, comparable to research-grade microscopes. This development enhances the utility of low-cost, portable microscopes for cellular imaging in educational and clinical settings.
研究不足
The study acknowledges potential artefacts due to the proprietary cellphone acquisition algorithm, which could affect the accuracy of focus measurements. The device's utility in field trials and its integration with other diagnostic tools are areas for future optimization.
1:Experimental Design and Method Selection:
The study involved designing a 3D-printed rack and pinion focussing mechanism for a ball lens-based microscope. The design was created using AutoDesk 123D Design and printed using an Ultimaker 2.0+ printer. The mechanism was tested for focus stability using an edge-based contrast measure.
2:0+ printer. The mechanism was tested for focus stability using an edge-based contrast measure.
Sample Selection and Data Sources:
2. Sample Selection and Data Sources: Samples included onion skin cells stained with Safranin, a thin smear of blood stained with Giemsa, and Plasmodium infected blood. Images were acquired using a cellphone camera and a research-grade microscope for comparison.
3:List of Experimental Equipment and Materials:
Equipment included a 3D printer (Ultimaker 2.0+), a Zeiss Axio Imager Z.1 microscope, and an LG G3 Smartphone. Materials included poly-lactic acid for printing, ball lenses, and various stains for sample preparation.
4:0+), a Zeiss Axio Imager Z.1 microscope, and an LG G3 Smartphone. Materials included poly-lactic acid for printing, ball lenses, and various stains for sample preparation.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The 3D-printed focussing mechanism was assembled and integrated with a paper microscope. Time-series images of samples were acquired to test focus stability. The edge-based contrast measure was used to quantify focus.
5:Data Analysis Methods:
Images were processed using ImageJ macros, and data were analyzed using Python and MATLAB scripts. The focus measure was calculated based on edge information in the images.
独家科研数据包,助您复现前沿成果,加速创新突破
获取完整内容