{"id":6447,"date":"2014-07-28T17:22:48","date_gmt":"2014-07-28T21:22:48","guid":{"rendered":"https:\/\/www.bu.edu\/cs\/?p=6447"},"modified":"2020-03-18T15:48:09","modified_gmt":"2020-03-18T19:48:09","slug":"margrit-betke-awarded-nsf-grant","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/cs\/2014\/07\/28\/margrit-betke-awarded-nsf-grant\/","title":{"rendered":"Margrit Betke awarded NSF grant"},"content":{"rendered":"<p>Professor Margrit Betke of the Computer Science Department received a National Science Foundation award entitled \u201cRI: Small: Using Humans in the Loop to Collect High-quality Annotations from Images and Time-lapse Videos of Cells.\u201d Congratulations to Margrit!<\/p>\n<p><strong>Abstract:<\/strong><br \/>\nSequences of microscopy images of live cells are analyzed by cell biologists to understand cellular processes, for example, to prevent cancer or design bio-materials for wound healing. Research progress is slowed or compromised when scientists find the image analysis efforts too labor-intensive to do themselves and the automation methods too numerous, unreliable, or difficult to use. The project develops image-analysis software to leverage human and computer resources together, in particular on the internet, to create high-quality image interpretations. An expansive benchmark study of detection, segmentation, and tracking algorithms for analyzing images of live cells is conducted, followed by the development of computer-vision approaches to the algorithms. Methods are designed for quantifying annotations, and then a tool is built to use the expertise of cell biologists to judge and select methods that analyze cell images. Crowd-sourcing experiments in which internet workers analyze images are designed and conducted. The quality of these lay workers&#8217; annotations is compared to the quality of annotations by cell biologists and automated methods. Finally, a machine learning system is developed that automatically determines which types of cell images or videos can be analyzed accurately with or without human involvement.<\/p>\n<p><a href=\"http:\/\/nsf.gov\/awardsearch\/showAward?AWD_ID=1421943\">Award Info<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Margrit Betke was awarded NSF grant on on crowdsourcing annotations of cell images<\/p>\n","protected":false},"author":6135,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/posts\/6447"}],"collection":[{"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/users\/6135"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/comments?post=6447"}],"version-history":[{"count":4,"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/posts\/6447\/revisions"}],"predecessor-version":[{"id":6451,"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/posts\/6447\/revisions\/6451"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/media?parent=6447"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/categories?post=6447"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/cs\/wp-json\/wp\/v2\/tags?post=6447"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}