WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
Browse
2 results
Search Results
Article Citation - WoS: 5Citation - Scopus: 9Image Processing and Cell Phone Microscopy to Analyze the Immunomagnetic Beads on Micro-Contact Printed Gratings(MDPI Ag, 2016-09-28) Icoz, KutayIn this paper we report an ultra-low-cost spherical ball lens based cell phone microscopy and image processing algorithms to analyze the amount of immunomagnetic beads on micro-contact printed gratings. The spherical ball lens provides approximately 100x magnification but the recorded images are not clear and are noisy. By using the image-processing algorithms, the noise can be reduced and the images can be enhanced to quantify the amount of immunomagnetic beads on micro-contact printed lines. This method, which is portable and low-cost, can be an alternative read out mechanism for biosensing applications using immunomagnetic beads on micro-contact printed surface receptors. Further, 0.0335 mg/mL was the lowest magnetic bead concentration that could be detected above the inherent noise level of the spherical ball lens.Article Citation - WoS: 22Citation - Scopus: 29Automated Quantification of Immunomagnetic Beads and Leukemia Cells from Optical Microscope Images(Elsevier Sci Ltd, 2019-03) Uslu, Fatma; Icoz, Kutay; Tasdemir, Kasim; Yilmaz, BulentQuantification of tumor cells is crucial for early detection and monitoring the progress of cancer. Several methods have been developed for detecting tumor cells. However, automated quantification of cells in the presence of immunomagnetic beads has not been studied. In this study, we developed computer vision based algorithms to quantify the leukemia cells captured and separated by micron size immunomagnetic beads. Color, size based object identification and machine learning based methods were implemented to quantify targets in the images recorded by a bright field microscope. Images acquired by a 40x or a 20x objective were analyzed, the immunomagnetic beads were detected with an error rate of 0.0171 and 0.0384 respectively. Our results reveal that the proposed method attains 91.6% precision for the 40x objective and 79.7% for the 20x objective. This algorithm has the potential to be the signal readout mechanism of a biochip for cell detection. (C) 2019 Elsevier Ltd. All rights reserved.