Portable and cost-effective pixel super-resolution on-chip microscope for telemedicine applications.
ABSTRACT We report a field-portable lensless on-chip microscope with a lateral resolution of <1 μm and a large field-of-view of ~24 mm(2). This microscope is based on digital in-line holography and a pixel super-resolution algorithm to process multiple lensfree holograms and obtain a single high-resolution hologram. In its compact and cost-effective design, we utilize 23 light emitting diodes butt-coupled to 23 multi-mode optical fibers, and a simple optical filter, with no moving parts. Weighing only ~95 grams, we demonstrate the performance of this field-portable microscope by imaging various objects including human malaria parasites in thin blood smears.
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ABSTRACT: A new approach toward increasing spatial resolution is required to overcome the limitations of the sensors and optics manufacturing technology. One promising approach is to use signal processing techniques to obtain an high-resolution (HR) image (or sequence) from observed multiple low-resolution (LR) images. Such a resolution enhancement approach has been one of the most active research areas, and it is called super resolution (SR) (or HR) image reconstruction or simply resolution enhancement. In this article, we use the term "SR image reconstruction" to refer to a signal processing approach toward resolution enhancement because the term "super" in "super resolution" represents very well the characteristics of the technique overcoming the inherent resolution limitation of LR imaging systems. The major advantage of the signal processing approach is that it may cost less and the existing LR imaging systems can be still utilized. The SR image reconstruction is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, including medical imaging, satellite imaging, and video applications. The goal of this article is to introduce the concept of SR algorithms to readers who are unfamiliar with this area and to provide a review for experts. To this purpose, we present the technical review of various existing SR methodologies which are often employed. Before presenting the review of existing SR algorithms, we first model the LR image acquisition process.IEEE Signal Processing Magazine 06/2003; 20(3-20):21 - 36. DOI:10.1109/MSP.2003.1203207 · 4.48 Impact Factor
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ABSTRACT: Some imaging systems employ detector arrays which are not sufficiently dense so as to meet the Nyquist criteria during image acquisition. This is particularly true for many staring infrared imagers. Thus, the full resolution afforded by the optics is not being realized in such a system. This paper presents a technique for estimating a high resolution image, with reduced aliasing, from a sequence of undersampled rotated and translationally shifted frames. Such an image sequence can be obtained if an imager is mounted on a moving platform, such as an aircraft. Several approaches to this type of problem have been proposed in the literature. Here we extend some of this previous work. In particular, we define an observation model which incorporates knowledge of the optical system and detector array. The high resolution image estimate is formed by minimizing a new regularized cost function which is based on the observation model. We show that with the proper choice of a tuning parameter, our algorithm exhibits robustness in the presence of noise. We consider both gradient descent and conjugate gradient optimization procedures to minimize the cost function. Detailed experimental results are provided to illustrate the performance of the proposed algorithm using digital video from an infrared imager.Optical Engineering 01/1998; 37(1). DOI:10.1117/1.601623 · 0.96 Impact Factor
Article: Lensfree microscopy on a cellphone.[Show abstract] [Hide abstract]
ABSTRACT: We demonstrate lensfree digital microscopy on a cellphone. This compact and light-weight holographic microscope installed on a cellphone does not utilize any lenses, lasers or other bulky optical components and it may offer a cost-effective tool for telemedicine applications to address various global health challenges. Weighing approximately 38 grams (<1.4 ounces), this lensfree imaging platform can be mechanically attached to the camera unit of a cellphone where the samples are loaded from the side, and are vertically illuminated by a simple light-emitting diode (LED). This incoherent LED light is then scattered from each micro-object to coherently interfere with the background light, creating the lensfree hologram of each object on the detector array of the cellphone. These holographic signatures captured by the cellphone permit reconstruction of microscopic images of the objects through rapid digital processing. We report the performance of this lensfree cellphone microscope by imaging various sized micro-particles, as well as red blood cells, white blood cells, platelets and a waterborne parasite (Giardia lamblia).Lab on a Chip 05/2010; 10(14):1787-92. DOI:10.1039/c003477k · 5.75 Impact Factor