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To achieve effective and scalable quantifications, we developed an automatic algorithm to quantify NO intensity for microphotographs taken from the experiments. Taking account of the special visual and geometric properties of microvessels in the study, the first step performs a novel Markov integrated dynamic programming procedure to single out the microvessel from the microphotograph. The next step applies image processing and morphological operations to identify ECs and TCs on the microvessel detected from the prior step. Finally, a normalized cross-correlation procedure is applied to register the TC map to the microvessel and evaluate the NO ratios in the ECs with and without TC adhesions. With a processing time reduced from hours to seconds, this algorithm evaluates NO ratios exceedingly similar to those by human operators. <\/jats:p>","DOI":"10.1142\/s0219467818500018","type":"journal-article","created":{"date-parts":[[2018,1,24]],"date-time":"2018-01-24T01:30:11Z","timestamp":1516757411000},"page":"1850001","source":"Crossref","is-referenced-by-count":1,"title":["Automatic Quantification of Endothelial Nitric Oxide Levels in a Microvessel with and without Tumor Cell Adhesion"],"prefix":"10.1142","volume":"18","author":[{"given":"Jie","family":"Wei","sequence":"first","affiliation":[{"name":"Department of Computer Science, City College of New York, New York 10031, USA"}]},{"given":"Lin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, City College of New York, New York 10031, USA"}]},{"given":"Bingmei M.","family":"Fu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, City College of New York, New York 10031, USA"}]}],"member":"219","published-online":{"date-parts":[[2018,1,23]]},"reference":[{"key":"S0219467818500018BIB001","volume-title":"Image Processing with ImageJ","author":"Perez J.","year":"2013"},{"key":"S0219467818500018BIB002","volume-title":"Introduction to Algorithms","author":"Cormen T. 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