Lensfree Computational Microscopy Tools and their Biomedical Applications
Jul 19, 2013
from 01:00 PM to 03:00 PM
|Contact Name||Carmen Chiuco|
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Advisor: Aydogan Ozcan
Conventional microscopy has been a revolutionary tool for biomedical applications since its invention several centuries ago. Ability to non-destructively observe very fine details of biological objects in real time enabled to answer many important questions about their structures and functions. Unfortunately, most of these advance microscopes are complex, bulky, expensive, and/or hard to operate, so they could not reach beyond the walls of well-equipped laboratories. Recent improvements in optoelectronic components and computational methods allow creating imaging systems that better fulfill the specific needs of clinics or research related biomedical applications. In this respect, lensfree computational microscopy aims to replace bulky and expensive optical components with compact and cost-effective alternatives through the use of computation, which can be particularly useful for lab-on-a-chip platforms as well as imaging applications in low-resource settings. This approach enabled us to build high-throughput on-chip platforms for applications including, but not limited to, cytometry, micro-array imaging, rare cell analysis, telemedicine, and water quality screening.
To achieve these goals, we used computational techniques that compensate for the lack of optical complexity in our lensfree on-chip imaging platforms. We utilized them for various purposes in our coherent, incoherent and fluorescent on-chip imaging platforms e.g. improving the spatial resolution, to undo the light diffraction without using lenses, localization of objects in a large volume and retrieval of the phase or the color/spectral content of the objects. One of these techniques is compressive sensing (or decoding), which is a novel method taking advantage of the fact that natural signals/objects are mostly sparse or compressible in known bases. This inherent property of objects enables better signal recovery when the number of measurement is low, even below the Nyquist rate, and increases the additive noise immunity of the system. Another computational tool employed in lensfree imaging is iterative phase retrieval. This technique enables recovering the complex optical field from its intensity measurement(s) by using additional constraints in iterations, such as spatial boundaries and other known properties of objects.
Ikbal Sencan completed her undergraduate study in Electronics Engineering, Fatih University, Istanbul in 2007 as Valedictorian. She received her M.S. degree in Electrical Engineering, UCLA in 2010. Currently, she is a PhD candidate in Nano/Biophotonics Laboratory under supervision of Prof. Aydogan Ozcan. Her research mainly focuses on high-throughput, high-resolution, low-cost, on-chip imaging and its biomedical applications with an emphasis on methods such as computational microscopy, fluorescent imaging cytometry, in-line holography, iterative phase retrieval, and compressive sensing. Her research on these fields has led to a book chapter, one patent and more than 40 peer-reviewed research articles in major scientific journals and conferences. Ikbal is the recipient of several undergraduate fellowships for students with outstanding rankings in nation-wide examinations and a prestigious graduate fellowship by Turkish Ministry of Education. She serves as a reviewer for PloS-ONE, Sensors & Actuators: B. Chemical, IEEE Global Humanitarian Technology Conference (GHTC). She is a member of IEEE, OSA, and SPIE.
Department Hosting: Electrical Engineering