Speckle-free laser imaging using random laser illumination

Many imaging applications require increasingly bright illumination sources, motivating the replacement of conventional thermal light sources with bright light-emitting diodes, superluminescent diodes and lasers. Despite their brightness, lasers and superluminescent diodes are poorly suited for full-field imaging applications because their high spatial coherence leads to coherent artefacts such as speckle that corrupt image formation. We recently demonstrated that random lasers can be engineered to provide low spatial coherence. Here, we exploit the low spatial coherence of specifically designed random lasers to demonstrate speckle-free full-field imaging in the setting of intense optical scattering. We quantitatively show that images generated with random laser illumination exhibit superior quality than images generated with spatially coherent illumination. By providing intense laser illumination without the drawback of coherent artefacts, random lasers are well suited for a host of full-field imaging applications from full-field microscopy to digital light projector systems.
To read the paper: http://www.nature.com/nphoton/journal/v6/n6/full/nphoton.2012.90.html

Compressive sensing resources: An emerging method for all

The dogma of signal processing maintains that a signal must be sampled at a rate at least twice its highest frequency in order to be represented without error. However, in practice, we often compress the data soon after sensing, trading off signal representation complexity (bits) for some error (consider JPEG image compression in digital cameras, for example). Clearly, this is wasteful of valuable sensing resources. Over the past few years, a new theory of "compressive sensing" has begun to emerge, in which the signal is sampled (and simultaneously compressed) at a greatly reduced rate.

As the compressive sensing research community continues to expand rapidly, it behooves us to heed Shannon's advice.

Compressive sensing is also referred to in the literature by the terms: compressed sensing, compressive sampling, and sketching/heavy-hitters.

The Compressive Sensing Resources: 

Rice University Resources: http://dsp.rice.edu/cs

Nuit Blanche Blog: http://nuit-blanche.blogspot.com/

CS 2.0 Blog: https://sites.google.com/site/igorcarron2/compressivesensing2.0

Compressive Sensing Research Groups:

The Rice group led by Richard Baraniuk has been the leader in spearheading information diffusion on the subject of compressive sensing through theirRice Compressive Sensing Resource page.  They also have a nice presentation of the now famous Rice Single pixel camera.

Terry Tao has made a list of the different matrices and their properties wrt compressive sensing in this page: Preprints in sparse recovery / Summary of properties of random matrices.

Face Recognition via Sparse Representation led by Yi Ma at UIUC

Feature Selection in Face Recognition: A Sparse Representation Perspectiveled by Allen Yang at Berkeley.

Duke DISP lab  led by David Brady. Of particular interest is Ashwin Wagadarikar's page on the compressive sensing hyperspectral imager.

Compressive Optical Systems, NISLab led by Rebecca Willett at Duke. 

Gabriel Peyre,  Chambolle's algorithm for the resolution of compressed sensing with TV regularization. 

Dror Baron's Compressed Sensing site. 

Faster STORM using compressed sensing

In super-resolution microscopy methods based on single-molecule switching, the rate of accumulating single-molecule activation events often limits the time resolution. Here we developed a sparse-signal recovery technique using compressed sensing to analyze images with highly overlapping fluorescent spots. This method allows an activated fluorophore density an order of magnitude higher than what conventional single-molecule fitting methods can handle. Using this method, we demonstrated imaging microtubule dynamics in living cells with a time resolution of 3 s. 

This work was published in Nature Methods.

Reference: http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.1978.html

Cellphone-based Diagnostic Technologies

In many third world and developing countries, the distance between people in need of health care and the facilities capable of providing it constitutes a major obstacle to improving health. One solution involves creating medical diagnostic applications small enough to fit into objects already in common use, such as cell phones — in effect, bringing the hospital to the patient. Here we list some of the emerging cell-phone based diagnostics technologies:

  1) Cell-phone lensfree microscope: UCLA researchers have advanced a novel lens-free, high-throughput imaging technique for potential use in such medical diagnostics, which promise to improve global disease monitoring, especially in resource-limited settings such as in Africa.
 Ref: http://pubs.rsc.org/en/content/articlelanding/2010/lc/c003477k

  2) Cell-phone imaging with microchip ELISA: Ovarian cancer is asymptomatic in the early stages and most patients present with advanced levels of disease. The lack of cost-effective methods that can achieve frequent, simple and non-invasive testing hinders early detection and causes high mortality in ovarian cancer patients. Here, we report a simple and inexpensive microchip ELISA-based detection module that employs a portable detection system, i.e., a cell phone/charge-coupled device (CCD) to quantify an ovarian cancer biomarker, HE4, in urine. Integration of a mobile application with a cell phone enabled immediate processing of microchip ELISA results, which eliminated the need for a bulky, expensive spectrophotometer.
 Ref: http://pubs.rsc.org/en/content/articlelanding/2011/lc/c1lc20479c

3) Mobile phone based clinical microscopy: Light microscopy provides a simple, cost-effective, and vital method for the diagnosis and screening of hematologic and infectious diseases. In many regions of the world, however, the required equipment is either unavailable or insufficiently portable, and operators may not possess adequate training to make full use of the images obtained. Counterintuitively, these same regions are often well served by mobile phone networks, suggesting the possibility of leveraging portable, camera-enabled mobile phones for diagnostic imaging and telemedicine. Toward this end 1we have built a mobile phone-mounted light microscope and demonstrated its potential for clinical use by imaging P. falciparum-infected and sickle red blood cells in brightfield and M. tuberculosis-infected sputum samples in fluorescence with LED excitation.
 Ref: http://www.plosone.org/article/info:doi/10.1371/journal.pone.0006320

 4) Cell-phone based platform as a biomedical device: In this paper we report the development of two attachments to a commercial cell phone that transform the phone's integrated lens and image sensor into a 350× microscope and visible-light spectrometer. The microscope is capable of transmission and polarized microscopy modes and is shown to have 1.5 micron resolution and a usable field-of-view of 150×150 with no image processing, and approximately 350×350 when post-processing is applied. The spectrometer has a 300 nm bandwidth with a limiting spectral resolution of close to 5 nm. We show applications of the devices to medically relevant problems.
 Ref: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0017150

5) Telemedicine tools with cell-phone cameras and paper microfluidics: This article describes a prototype system for quantifying bioassays and for exchanging the results of the assays digitally with physicians located off-site. The system uses paper-based microfluidic devices for running multiple assays simultaneously, camera phones or portable scanners for digitizing the intensity of color associated with each colorimetric assay, and established communications infrastructure for transferring the digital information from the assay site to an off-site laboratory for analysis by a trained medical professional; the diagnosis then can be returned directly to the healthcare provider in the field.
 Ref: http://pubs.acs.org/doi/abs/10.1021/ac800112r

 And also other technologies are coming up soon by various researchers...

Bleaching/blinking assisted localization microscopy

Superresolution imaging techniques based on the precise localization of single molecules, such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), achieve high resolution by fitting images of single fluorescent molecules with a theoretical Gaussian to localize them with a precision on the order of tens of nanometers. PALM/STORM rely on photoactivated proteins or photoswitching dyes, respectively, which makes them technically challenging. We present a simple and practical way of producing point localization-based superresolution images that does not require photoactivatable or photoswitching probes. Called bleaching/blinking assisted localization microscopy (BaLM), the technique relies on the intrinsic bleaching and blinking behaviors characteristic of all commonly used fluorescent probes. To detect single fluorophores, we simply acquire a stream of fluorescence images. Fluorophore bleach or blink-off events are detected by subtracting from each image of the series the subsequent image. Similarly, blink-on events are detected by subtracting from each frame the previous one. After image subtractions, fluorescence emission signals from single fluorophores are identified and the localizations are determined by fitting the fluorescence intensity distribution with a theoretical Gaussian. We also show that BaLM works with a spectrum of fluorescent molecules in the same sample. Thus, BaLM extends single molecule-based superresolution localization to samples labeled with multiple conventional fluorescent probes. For more: Biological Sciences - Cell Biology: Dylan T. Burnette, Prabuddha Sengupta, Yuhai Dai, Jennifer Lippincott-Schwartz, and Bechara Kachar Bleaching/blinking assisted localization microscopy for superresolution imaging using standard fluorescent molecules PNAS 2011 108 (52) 21081-21086; published ahead of print December 13, 2011, doi:10.1073/pnas.1117430109

Optogenetics: controlling cell function with light

Nature method's method of the year 2010 has been announced on an emerging method that is called Optogenetics. The combination of genetic and optical methods enabled scientists to explore biological processes with high temporal and cell-specific resolution. Not only neuroscience but also other cell/tissue related fields have now started to utilize optogenetics to open new landscapes for the study of biology.
Here is the video explaining the method of optogenetics:


Here you can reach to the news, articles and reviews on this promising method: MOY 2010, Nature Method

You may want to also visit the Stanford optogenetics resources

Finally, here are the recent articles on optogenetics:

(1) Global and local fMRI signals driven by neurons defined optogenetically by type and wiring, Nature 2010

(2) Optogenetics: Controlling the Brain with Light , Scientific American 2010

(3)Decoding the Brain with Light, Technology Review, 2009

(4)Optogenetics 3.0, Cell 2010

(5)Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures, Nature Protocols 2010

Protein localization using electron and fluorescence nanoscopy

Molecular topography of a cell can be successfully monitored by combining powerful imaging techniques such as electron microscopy and fluorescence nanoscopy ( STED or PALM). Recently, Prof. Erik M Jorgensen and his colleagues described a correlative fluorescence electron microscopy technique to localize protein on specific organelles. Here organelles first are revealed by electron microscopy and proteins are monitored by fluorescence imaging. As a result of image correlation between these two imaging modalities, proteins can be localized with nanometer accuracy. The paper also demonstrates localization of histone proteins on mitochondria.

Here is the paper that was published in Nature Methods: "Protein localization in electron micrographs using fluorescence nanoscopy"