A convolutional neural network based single-frame super-resolution for lensless blood cell counting
Xiwei Huang, Yu Sherry Jiang, Hang Xu, Xu Liu, Han Wei Hou, Yan Mei, Hao Yu · 2016
This paper presents one Convolutional Neural Network based single-frame Super-Resolution processing (CNNSR) for lensless blood cell counting, which takes one single low-resolution cell shadow image as the input and outputs an improved high-resolution one for better cell detection. Due to the advantage of lightweight and fully feed-forward structure, CNNSR is highly efficient and requires minimum resource for hardware implementation. One lensless imaging prototype integrating a 1.1-μm pixel-pitch back-side illuminated (BSI) CMOS image sensor and a microfluidic channel is further demonstrated, which shows clear detection of <;2-μm platelet cells in the blood sample solution for point-of-care diagnostics.