Image Sensor System for Detection of Bacteria and Antibiotic Resistance
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Bildsensorsystem för detektion av bakterier och antibiotikaresistens (Swedish)
Antibiotic resistance is now a recognized problem in global health. In attempts to find solutions to detect bacteria causing antibiotic resistance we turn to technological solutions that are miniaturized, portable and cheap. The current diagnostic procedures cannot provide correct information outside laboratory settings, at the point-of-care, within necessary time. This has led to ineffective treatment of urinary tract infections causing recurrent infections and multi-drug resistant bacteria to spread. The bacteria genes show which antibiotic that is required to eliminate disease and spread of resistance. Hence, the solution would be to perform nucleic acid testing at the point-of-care. By using new DNA amplification methods it is possible to miniaturize the diagnostic test to a so-called Lab-on-a-chip. These solutions would enable sample-in-results-out capability of the system at the point-of-care. For this to work one of the most important factors is fluorescent signal read-out from DNA amplification products.
In this project the design parameters of such a read-out device was investigated with focus on image sensor sensitivity and device integration. During the project it was found that a low-cost commercial image sensor could be used to record images of a (3.76 x 2.74 mm2) micro well array of nanoliter sized PCR chambers. Different imaging artifacts appearing during sample partitioning were observed, distance dependency between sensor surface well array was investigate, and finally the image sensor function was compared to a fluorescent microscope.
Place, publisher, year, edition, pages
2015. , 88 p.
CMOS, CCD, image sensor, fluorescence imaging, Lab-on-a-chip, digitalPCR, urinary tract infections, point-of-care
IdentifiersURN: urn:nbn:se:kth:diva-179399OAI: oai:DiVA.org:kth-179399DiVA: diva2:882871
Subject / course
Master of Science in Engineering - Medical Engineering
Vastesson, Alexander, PhD Student
Nilsson, Mats, PhD