Researchers at the UCLA Samueli School of Engineering have demonstrated that deep learning， a powerful form of artificial intelligence， can discern and enhance microscopic details in photos taken by smartphones. The technique improves the resolution and color details of smartphone images so much that they approach the quality of images from laboratory-grade microscopes.

加州大学洛杉矶分校（UCLA）萨缪尔工程学院的研究人员展示了“深度学习”这一强大的人工智能技术，它能辨识并增强智能手机所摄照片的微观细节。这项技术可以显著提升智能手机图像的分辨率和色彩细节，使图像质量逼近实验室级显微镜所摄图像。

The advance could help bring high-quality medical diagnostics into resource-poor regions， where people otherwise do not have access to high-end diagnostic technologies. And the technique uses attachments that can be inexpensively produced with a 3-D printer， at less than $100 a piece， versus the thousands of dollars it would cost to buy laboratory-grade equipment that produces images of similar quality.

这一进步可能助推高质量医疗诊断进入资源匮乏的地区，那些地区的居民目前享受不到高端诊断技术带来的好处。而且，这项技术使用的附件可以通过3D打印机生产，价格低廉，每件成本不足100美元。相比之下，购置能生成具有类似质量图像的实验室级设备需要花费数千美元。

Cameras on today’s smartphones are designed to photograph people and scenery， not to produce high-resolution microscopic images. So the researchers developed an attachment that can be placed over the smartphone lens to increase the resolution and the visibility of tiny details of the images they take， down to a scale of approximately one millionth of a meter.

如今，智能手机上的摄像头主要用于拍摄人物和风景，而不是生成高分辨率的显微图像。