ABSTRACT
Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240 Overview of Different Lensfree On-Chip Imaging Systems . . . . . . . . . . . . . . 240
On-Chip Fluorescence and Incoherent Microscopy . . . . . . . . . . . . . . . . . . 240 Partially Coherent On-Chip Holographic Microscopy . . . . . . . . . . . . . . . . 243
Application Examples on the Use of Compressive Decoding in Lensfree On-Chip Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
On-Chip Incoherent Microscopy Applications Using FLUOCHIP and MONA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
High-Throughput Dual-Mode Imaging of Transgenic Caenorhabditis elegans Using FLUOCHIP . . . . . . . . . . . . . . . . . . . . . . 246 Color Imaging Using FLUOCHIP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248 FLUOCHIP with Fiber-Optic Faceplates and Tapers. . . . . . . . . . . . . . . 249 Incoherent Microscopy with On-Chip Nano-Apertures. . . . . . . . . . . . . 249 Multicolor MONA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
Spectral Demultiplexing of Sunlight Holograms . . . . . . . . . . . . . . . . . . . . 253 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257
Introduction Recent advances in light microscopy (Betzig et al. 2006; Gustafsson 2005; Hell 2003; Hess et al. 2006; Rust et al. 2006) transformed our toolset in biomedical research and clinical problems. Nowadays, optical microscopes are routinely used to nondestructively observe live biological samples with high spatial and temporal resolution. However, the overall space-bandwidth product of these imaging platforms is usually limited (Neifeld 1998), and users need to often trade off between spatial resolution and field of view, depending on the application. Moreover, most advanced microscopes are still relatively complex, expensive, and bulky. All these factors hinder easy access to advanced light microscopes at resource-limited settings or developing countries. Computational imaging, particularly lensfree onchip microscopy, aims to democratize access to advanced optical microscopy tools by offering imaging platforms with high space-bandwidth products, low operational complexity and costs (Ozcan 2014). These unique advantages result from the simplicity of the on-chip imaging design of these lensfree platforms and the lack of expensive optical components. One should also note that the structural simplicity of lensfree on-chip microscopy also brings challenges that can be addressed computationally (Greenbaum et al. 2012). Lensfree microscopy platforms provide imaging solutions, which are portable for field use, compatible with lab-on-a-chip devices, and provide extremely wide field of view to address various challenges and needs of global health, telemedicine, and microfluidics/ lab-on-achip applications, among others (Greenbaum et al. 2013; Mudanyali et al. 2010; Seo et al. 2010; Su et al. 2010; Zhu et al. 2013).
