A new cell counter uses the imaging chip
from a digital camera to record the “shadows,” or diffraction signatures

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.
 
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.
The technique is known as Lensless Ultra-wide-field Cell monitoring Array based on Shadow imaging (LUCAS) technique. Removing the lens from the imaging process allows LUCAS to be scaled down to the point that it can eventually be integrated into a regular wireless cell phone. Samples could be loaded into a specially equipped phone using a disposable microfluidic chip.
 
The UCLA researchers have now improved the LUCAS technique to the point that it can classify a significantly larger sample volume than previously shown — up to 5 milliliters, from an earlier volume of less than 0.1 ml — representing a major step toward portable medical diagnostic applications.
 
The research team envisions people one day being able to draw a blood sample into a chip the size of a quarter, which could then be inserted into a LUCAS-equipped cell phone that would quickly identify and count the cells within the sample. The read-out could be sent wirelessly to a hospital for further analysis.
 
LUCAS functions as an imaging scheme in which the shadow of each cell in an entire sample volume is detected in less than a second. The acquired shadow image is then digitally processed using a custom-developed "decision algorithm" to enable both the identification of the cell/bacteria location in 3-D and the classification of each microparticle type within the sample volume.
 
Various cell types — such as red blood cells, fibroblasts and hepatocytes — or other microparticles, such as bacteria, all exhibit uniquely different shadow patterns and therefore can be rapidly identified using the decision algorithm.
 
Another improvement detailed in the UCLA research is the creation of a hybrid imaging scheme that combines two different wavelengths to further improve the digital quality of shadow images. This new cell classification scheme has been termed "multicolor LUCAS." As the team illustrated, further improvement in image quality can also be achieved through the use of adaptive digital filtering. As result of these upgrades, the volume of the sample solution that can be imaged has been increased, as mentioned, from less than 0.1 ml to 5 ml.