OpenCFU, a New Free and Open-Source Software to Count Cell Colonies and Other Circular Objects
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{"title"=>"OpenCFU, a New Free and Open-Source Software to Count Cell Colonies and Other Circular Objects", "type"=>"journal", "authors"=>[{"first_name"=>"Quentin", "last_name"=>"Geissmann", "scopus_author_id"=>"55601682000"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"368367906", "sgr"=>"84874046979", "scopus"=>"2-s2.0-84874046979", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"23457446", "doi"=>"10.1371/journal.pone.0054072", "issn"=>"19326203"}, "id"=>"36598040-51e9-3901-bfd3-52355681ec2a", "abstract"=>"Counting circular objects such as cell colonies is an important source of information for biologists. Although this task is often time-consuming and subjective, it is still predominantly performed manually. The aim of the present work is to provide a new tool to enumerate circular objects from digital pictures and video streams. Here, I demonstrate that the created program, OpenCFU, is very robust, accurate and fast. In addition, it provides control over the processing parameters and is implemented in an intuitive and modern interface. OpenCFU is a cross-platform and open-source software freely available at http://opencfu.sourceforge.net.", "link"=>"http://www.mendeley.com/research/opencfu-new-free-opensource-software-count-cell-colonies-other-circular-objects", "reader_count"=>133, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Researcher"=>29, "Student > Doctoral Student"=>12, "Student > Ph. D. Student"=>35, "Student > Postgraduate"=>8, "Student > Master"=>18, "Other"=>3, "Student > Bachelor"=>18, "Lecturer"=>3, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Researcher"=>29, "Student > Doctoral Student"=>12, "Student > Ph. D. Student"=>35, "Student > Postgraduate"=>8, "Student > Master"=>18, "Other"=>3, "Student > Bachelor"=>18, "Lecturer"=>3, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>7, "Agricultural and Biological Sciences"=>64, "Philosophy"=>1, "Chemical Engineering"=>1, "Chemistry"=>8, "Computer Science"=>8, "Earth and Planetary Sciences"=>1, "Engineering"=>8, "Environmental Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>18, "Mathematics"=>1, "Medicine and Dentistry"=>6, "Neuroscience"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>3, "Physics and Astronomy"=>2, "Immunology and Microbiology"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>6}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>7}, "Environmental Science"=>{"Environmental Science"=>2}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>3}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Engineering"=>{"Engineering"=>8}, "Chemistry"=>{"Chemistry"=>8}, "Neuroscience"=>{"Neuroscience"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>64}, "Computer Science"=>{"Computer Science"=>8}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>18}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"United States"=>2, "Philippines"=>2, "Japan"=>1, "United Kingdom"=>4, "Spain"=>1, "Sweden"=>1, "Norway"=>1, "Luxembourg"=>1, "Brazil"=>1, "Denmark"=>1, "South Africa"=>1, "Australia"=>1, "Chile"=>1, "Germany"=>1, "Indonesia"=>2}, "group_count"=>2}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/487056"], "description"=>"<p>The image is preprocessed (1) in order to correct for gradual changes in background intensity and increase the contrast. The first pass of the processing (2) generates a score-map by iteratively annotating valid regions. The second pass (3) involves finding connected components in the thresholded score-map and segmenting them using a distance transform/watershed approach. Optional postprocessing filters (4) can be performed by OpenCFU or, using the raw data, by the user.</p>", "links"=>[], "tags"=>["microbiology", "biotechnology", "computer science", "pathology"], "article_id"=>157581, "categories"=>["Information And Computing Sciences", "Biotechnology", "Cell Biology", "Microbiology"], "users"=>["Quentin Geissmann"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0054072.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flowchart_representing_the_processing_steps_/157581", "title"=>"Flowchart representing the processing steps.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 15:13:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/487173"], "description"=>"<p>Each channel of the original image (A) is preprocessed individually and merged to a grey-scale image (B). A score-map is generated by recursive thresholding an annotation of circular regions (C). This excludes regions that were morphologically unlikely to be colonies (<i>i.e</i>. arrows 1 and 2). The score-map is then thresholded by a user-defined or automatically calculated value (D). The objects identified as merged colonies (on the basis of their morphological features) are segmented using a watershed variant on their distance transform (E). Arrow 3 shows objects that have been successfully segmented. Finally, the morphologically valid objects can be assessed further using intensity and colour filters. Arrow 4 shows a minority contaminant bacteria that was excluded using postprocessing filter and represented by crossed-out red ellipses. Arrow 5 shows valid colonies represented by yellow and blue ellipses. For the purpose of explanation, only representative areas (200200 pixels) of three processed images are shown here.</p>", "links"=>[], "tags"=>["steps", "performed"], "article_id"=>157700, "categories"=>["Information And Computing Sciences", "Biotechnology", "Cell Biology", "Microbiology"], "users"=>["Quentin Geissmann"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0054072.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustration_of_the_processing_steps_performed_on_three_sample_images_/157700", "title"=>"Illustration of the processing steps performed on three sample images.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 15:14:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/487298"], "description"=>"<p>An original arbitrary square image was either tiled to itself or scaled-up (A) in order to obtain a range of square images featuring an increasing number of colonies or increasingly large colonies, respectively. The processing time of the three methods for these images was estimated in both cases (B). On the tested range of resolutions, OpenCFU was faster than both NICE and the ImageJ macro (IJM). The segments joining points do not represent data, but only aid readability.</p>", "links"=>[], "tags"=>["imagej", "macro", "images"], "article_id"=>157825, "categories"=>["Information And Computing Sciences", "Biotechnology", "Cell Biology", "Microbiology"], "users"=>["Quentin Geissmann"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0054072.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Processing_time_of_OpenCFU_NICE_13_and_an_ImageJ_macro_10_for_images_of_different_size_/157825", "title"=>"Processing time of OpenCFU, NICE [13] and an ImageJ macro [10] for images of different size.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 15:14:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/487416"], "description"=>"<p>The medians of seven humans counts were used as a reference to measure deviation. The effect of the number of colonies on the deviation from the reference was assessed (A). For NICE and the ImageJ macro (IJM), the slope was significantly negative. The dotted line represents the reference. The absolute deviation from the reference was used as a measure of error (B). Error for the best human, the worst human and the three methods were compared to the pooled human group. With high-definition images (HD), NICE and IJM had a higher error than the pooled human group (Pool) while OpenCFU (OFU) did not. Using low-definition pictures (LD) from a low-cost webcam increased the error for the three methods.</p>", "links"=>[], "tags"=>["imagej", "macro"], "article_id"=>157946, "categories"=>["Information And Computing Sciences", "Biotechnology", "Cell Biology", "Microbiology"], "users"=>["Quentin Geissmann"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0054072.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_accuracy_between_OpenCFU_NICE_13_and_an_ImageJ_macro_10_/157946", "title"=>"Comparison of accuracy between OpenCFU, NICE [13] and an ImageJ macro [10].", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 15:15:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/487577"], "description"=>"<p>A qualitative assessment of robustness was undertaken by analysing pictures containing artefacts (A). Representative portions of 1.7 cm by 1.7 cm (200200 pixels) illustrate the results of the presence of bubbles (1), cracks in the agar (2), dust (3) and edge of dish (4) in the region of interest. Objects detected by OpenCFU, NICE and the ImageJ macro (IJM) are represented by ellipses, crosses and arbitrary colours, respectively. NICE and IJM but not OpenCFU seemed to consistently detect artefacts as colonies. A quantitative analysis of robustness to plate mispositioning was conducted (B). OpenCFU, NICE and IJM were used to count the number of colonies in the pictures of 19 plates. Then, all the images were translated by 1.7 mm (25px) and analysed with the same region of interest as the original. This procedure induced a significant bias for NICE, (-) colonies and IJM (-) colonies, but not for OpenCFU (-) colonies (one-sided paired t-test). The impact of the presence of bubbles in the agar was measured by analysing pictures of 18 plates containing exclusively bubbles (C). A linear regression between the number of bubbles and the number of detected objects was performed. NICE and IJM counts were both positively related to the number of bubbles, (-) and (-), respectively. OpenCFU was not affected: (-.</p>", "links"=>[], "tags"=>["robustness", "perturbations", "imagej", "macro"], "article_id"=>158102, "categories"=>["Information And Computing Sciences", "Biotechnology", "Cell Biology", "Microbiology"], "users"=>["Quentin Geissmann"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0054072.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_robustness_to_common_perturbations_between_OpenCFU_NICE_13_and_an_ImageJ_macro_10_/158102", "title"=>"Comparison of robustness to common perturbations between OpenCFU, NICE [13] and an ImageJ macro [10].", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 15:16:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/487722"], "description"=>"<p>A qualitative assessment of the versatility of OpenCFU was undertaken by analysing pictures of different circular biological objects: a clear (A) and a poor quality (B) picture of <i>Staphylococcus aureus</i> colonies, a low-contrasted picture of <i>Escherichia coli</i> (C), a noisy picture of mustard seeds (D), a noisy picture of soy-bean seeds (E), and a micrography of <i>Carduus sp</i>. pollen (F). For the purpose of explanation, only representative areas (200200 pixels) of six processed images are shown here. Original portions of images are on the left and correspond to the graphical results obtained using OpenCFU on the right.</p>", "links"=>[], "tags"=>["microbiology", "biotechnology", "computer science", "pathology"], "article_id"=>158245, "categories"=>["Information And Computing Sciences", "Biotechnology", "Cell Biology", "Microbiology"], "users"=>["Quentin Geissmann"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0054072.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Versatility_of_OpenCFU_/158245", "title"=>"Versatility of OpenCFU.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 15:16:57"}

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Relative Metric

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