High-throughput Computer Method for 3D Neuronal Structure Reconstruction from the Image Stack of the Drosophila Brain and Its Applications
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{"title"=>"High-throughput Computer Method for 3D Neuronal Structure Reconstruction from the Image Stack of the Drosophila Brain and Its Applications", "type"=>"journal", "authors"=>[{"first_name"=>"Ping Chang", "last_name"=>"Lee", "scopus_author_id"=>"24766381700"}, {"first_name"=>"Chao Chun", "last_name"=>"Chuang", "scopus_author_id"=>"7201496309"}, {"first_name"=>"Ann Shyn", "last_name"=>"Chiang", "scopus_author_id"=>"7101623560"}, {"first_name"=>"Yu Tai", "last_name"=>"Ching", "scopus_author_id"=>"7005431288"}], "year"=>2012, "source"=>"PLoS Computational Biology", "identifiers"=>{"scopus"=>"2-s2.0-84866912879", "doi"=>"10.1371/journal.pcbi.1002658", "pui"=>"365755948", "issn"=>"1553734X", "pmid"=>"23028271", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)", "sgr"=>"84866912879"}, "id"=>"c2658c30-6c08-3da9-98e8-ba06e1d0218e", "abstract"=>"Drosophila melanogaster is a well-studied model organism, especially in the field of neurophysiology and neural circuits. The brain of the Drosophila is small but complex, and the image of a single neuron in the brain can be acquired using confocal microscopy. Analyzing the Drosophila brain is an ideal start to understanding the neural structure. The most fundamental task in studying the neural network of Drosophila is to reconstruct neuronal structures from image stacks. Although the fruit fly brain is small, it contains approximately 100,000 neurons. It is impossible to trace all the neurons manually. This study presents a high-throughput algorithm for reconstructing the neuronal structures from 3D image stacks collected by a laser scanning confocal microscope. The proposed method reconstructs the neuronal structure by applying the shortest path graph algorithm. The vertices in the graph are certain points on the 2D skeletons of the neuron in the slices. These points are close to the 3D centerlines of the neuron branches. The accuracy of the algorithm was verified using the DIADEM data set. This method has been adopted as part of the protocol of the FlyCircuit Database, and was successfully applied to process more than 16,000 neurons. This study also shows that further analysis based on the reconstruction results can be performed to gather more information on the neural network.", "link"=>"http://www.mendeley.com/research/highthroughput-computer-method-3d-neuronal-structure-reconstruction-image-stack-drosophila-brain-app", "reader_count"=>57, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>2, "Student > Doctoral Student"=>3, "Researcher"=>15, "Student > Ph. D. Student"=>24, "Student > Postgraduate"=>2, "Other"=>1, "Student > Master"=>3, "Student > Bachelor"=>3, "Professor"=>4}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>2, "Student > Doctoral Student"=>3, "Researcher"=>15, "Student > Ph. D. Student"=>24, "Student > Postgraduate"=>2, "Other"=>1, "Student > Master"=>3, "Student > Bachelor"=>3, "Professor"=>4}, "reader_count_by_subject_area"=>{"Engineering"=>9, "Biochemistry, Genetics and Molecular Biology"=>4, "Agricultural and Biological Sciences"=>18, "Medicine and Dentistry"=>2, "Neuroscience"=>5, "Sports and Recreations"=>1, "Physics and Astronomy"=>5, "Social Sciences"=>1, "Computer Science"=>12}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>9}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Neuroscience"=>{"Neuroscience"=>5}, "Social Sciences"=>{"Social Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>5}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>18}, "Computer Science"=>{"Computer Science"=>12}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}}, "reader_count_by_country"=>{"Canada"=>1, "Netherlands"=>1, "Japan"=>3, "Australia"=>1, "Portugal"=>1, "Germany"=>1}, "group_count"=>2}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/576992"], "description"=>"<p>The references are respectively our reconstruction (top) and the ground truth (bottom).</p>", "links"=>[], "tags"=>["histograms", "distances", "points", "reconstructed"], "article_id"=>247491, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g004", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_These_two_histograms_show_the_distribution_of_the_distances_between_points_on_one_reconstructed_result_and_a_reference_reconstruction_/247491", "title"=>"These two histograms show the distribution of the distances between points on one reconstructed result and a reference reconstruction.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:04:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/577716"], "description"=>"<p>The black nodes represent the points in Q.</p>", "links"=>[], "tags"=>["nodes", "points"], "article_id"=>248214, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g011", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_black_nodes_represent_the_points_in_Q_/248214", "title"=>"The black nodes represent the points in Q.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:16:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/577896"], "description"=>"<p>Parameters for reconstruction.</p>", "links"=>[], "tags"=>["computer science"], "article_id"=>248395, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.t002", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Parameters_for_reconstruction_/248395", "title"=>"Parameters for reconstruction.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-09-13 02:19:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/577135"], "description"=>"<p>The green rectangles indicate the regions where the large distances occur.</p>", "links"=>[], "tags"=>["reconstruction", "tracing", "overlap", "rendering"], "article_id"=>247629, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g005", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Both_the_gold_reconstruction_top_and_our_tracing_result_bottom_overlap_with_the_volume_rendering_of_the_original_image_stack_are_shown_/247629", "title"=>"Both the gold reconstruction (top) and our tracing result (bottom) overlap with the volume rendering of the original image stack are shown.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:07:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/577386"], "description"=>"<p>We can find that the distributions of five noise levels are almost the same.</p>", "links"=>[], "tags"=>["histogram"], "article_id"=>247886, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g007", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_histogram_for_all_five_different_noise_levels_/247886", "title"=>"The histogram for all five different noise levels.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:11:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/577778"], "description"=>"<p>The green rectangles indicate the somas.</p>", "links"=>[], "tags"=>["removing", "branches", "soma"], "article_id"=>248271, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g012", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_results_of_before_left_and_after_right_removing_short_branches_inside_the_soma_are_demonstrated_/248271", "title"=>"The results of before (left) and after (right) removing short branches inside the soma are demonstrated.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:17:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/577842"], "description"=>"<p>The lines in (a) are zigzag shaped. However, they become smooth when the ε-approximation method is applied (b). The <i>ε</i> was .</p>", "links"=>[], "tags"=>["zoom-in", "traced", "lines", "tracing"], "article_id"=>248336, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g013", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_zoom_in_view_of_the_traced_result_Red_lines_show_the_tracing_results_/248336", "title"=>"A zoom-in view of the traced result. Red lines show the tracing results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:18:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/303651", "https://ndownloader.figshare.com/files/303728", "https://ndownloader.figshare.com/files/303799"], "description"=>"<div><p><em>Drosophila melanogaster</em> is a well-studied model organism, especially in the field of neurophysiology and neural circuits. The brain of the <em>Drosophila</em> is small but complex, and the image of a single neuron in the brain can be acquired using confocal microscopy. Analyzing the <em>Drosophila</em> brain is an ideal start to understanding the neural structure. The most fundamental task in studying the neural network of <em>Drosophila</em> is to reconstruct neuronal structures from image stacks. Although the fruit fly brain is small, it contains approximately 100 000 neurons. It is impossible to trace all the neurons manually. This study presents a high-throughput algorithm for reconstructing the neuronal structures from 3D image stacks collected by a laser scanning confocal microscope. The proposed method reconstructs the neuronal structure by applying the shortest path graph algorithm. The vertices in the graph are certain points on the 2D skeletons of the neuron in the slices. These points are close to the 3D centerlines of the neuron branches. The accuracy of the algorithm was verified using the DIADEM data set. This method has been adopted as part of the protocol of the <em>FlyCircuit</em> Database, and was successfully applied to process more than 16 000 neurons. This study also shows that further analysis based on the reconstruction results can be performed to gather more information on the neural network.</p> </div>", "links"=>[], "tags"=>["high-throughput", "3d", "neuronal", "reconstruction", "applications"], "article_id"=>119891, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002658.s001", "https://dx.doi.org/10.1371/journal.pcbi.1002658.s002", "https://dx.doi.org/10.1371/journal.pcbi.1002658.s003"], "stats"=>{"downloads"=>7, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/High_throughput_Computer_Method_for_3D_Neuronal_Structure_Reconstruction_from_the_Image_Stack_of_the_Drosophila_Brain_and_Its_Applications/119891", "title"=>"High-throughput Computer Method for 3D Neuronal Structure Reconstruction from the Image Stack of the <em>Drosophila</em> Brain and Its Applications", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-09-13 02:44:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/577652"], "description"=>"<p>(a) The MIP image of the original image stack. (b) Red dot indicates the center of the soma calculated by the soma detection procedure. (c) A close view of the detected soma position.</p>", "links"=>[], "tags"=>["soma"], "article_id"=>248150, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g010", "stats"=>{"downloads"=>3, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_An_example_of_the_soma_detection_/248150", "title"=>"An example of the soma detection.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:15:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/577275"], "description"=>"<p>The images were contaminated by different levels of Gaussian noise: (a) σ = 20, (b) σ = 30, (c) σ = 40, (d) σ = 50, and (e) σ = 60.</p>", "links"=>[], "tags"=>["images", "contaminated", "levels", "gaussian"], "article_id"=>247771, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g006", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_images_were_contaminated_by_different_levels_of_Gaussian_noise_a_963_8202_8202_20_b_963_8202_8202_30_c_963_8202_8202_40_d_963_8202_8202_50_and_e_963_8202_8202_60_/247771", "title"=>"The images were contaminated by different levels of Gaussian noise: (a) σ = 20, (b) σ = 30, (c) σ = 40, (d) σ = 50, and (e) σ = 60.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:09:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/576575"], "description"=>"<p>For the purpose of comparison, the result is translated a little from its original position.</p>", "links"=>[], "tags"=>["rendered", "traced", "neuron", "overlaps", "rendering"], "article_id"=>247067, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_rendered_traced_result_red_of_a_neuron_overlaps_with_the_volume_rendering_of_the_original_image_stack_/247067", "title"=>"The rendered traced result (<i>red</i>) of a neuron overlaps with the volume rendering of the original image stack.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 01:57:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/577929"], "description"=>"<p>Reconstruction time and accuracy.</p>", "links"=>[], "tags"=>["computer science"], "article_id"=>248424, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.t001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Reconstruction_time_and_accuracy_/248424", "title"=>"Reconstruction time and accuracy.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-09-13 02:20:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/576713"], "description"=>"<p>Both (a) and (b) show the neurons (top) and the traced results (bottom). The projection neuron connecting optical lobes has dense branches and complex morphology. In addition, the intensity of the neuron in (a) has a wide dynamic range. The proposed method can manage these situations and make necessary corrections. When the whole process is completed, the reconstructions of both neurons are complete with high fidelity.</p>", "links"=>[], "tags"=>["reconstruction", "optical", "nerves"], "article_id"=>247209, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g002", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Two_reconstruction_results_of_optical_nerves_were_demonstrated_/247209", "title"=>"Two reconstruction results of optical nerves were demonstrated.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:00:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/577524"], "description"=>"<p>The neurons are rendered by the maximum intensity projection (MIP) method. Every row shows a neuron undergoing different levels of binarization. From left to right, they are the original neuron image followed by the binarized results. From the second column to the last column, we kept 50%, 60%, 70%, and 80% of the brightest visible voxels where the visible voxels are voxels having a gray scale above 10. In the proposed method, we keep 70% of the brightest visible voxels, which are shown in column 4.</p>", "links"=>[], "tags"=>["diadem", "binarization"], "article_id"=>248019, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g009", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Three_data_of_Olfactory_Projection_Neuron_in_the_DIADEM_data_set_are_used_to_demonstrate_the_binarization_method_/248019", "title"=>"Three data of <i>Olfactory Projection Neuron</i> in the DIADEM data set are used to demonstrate the binarization method.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:13:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/576863"], "description"=>"<p>Totally 198 olfactory PNs in the right hemisphere and 203 olfactory PNs in the left hemisphere were selected.</p>", "links"=>[], "tags"=>["olfactory", "pns", "computed", "tract", "clusters", "neuron", "overlapping"], "article_id"=>247353, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g003", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_An_illustration_of_olfactory_PNs_collection_left_the_computed_tract_clusters_upper_right_and_the_neuron_image_clusters_overlapping_the_computed_cluster_lower_right_/247353", "title"=>"An illustration of olfactory PNs collection (left), the computed tract clusters (upper right) and the neuron image clusters overlapping the computed cluster (lower right).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:02:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/577439"], "description"=>"<p>The traced result (<i>red</i>) of the contaminated, σ = 60 image stack overlaps with the volume rendering of the image stack.</p>", "links"=>[], "tags"=>["traced", "overlaps", "rendering"], "article_id"=>247933, "categories"=>["Information And Computing Sciences"], "users"=>["Ping-Chang Lee", "Chao-Chun Chuang", "Ann-Shyn Chiang", "Yu-Tai Ching"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002658.g008", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_traced_result_red_of_the_contaminated__60_image_stack_overlaps_with_the_volume_rendering_of_the_image_stack_/247933", "title"=>"The traced result (<i>red</i>) of the contaminated, σ = 60 image stack overlaps with the volume rendering of the image stack.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-09-13 02:12:13"}

PMC Usage Stats | Further Information

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Relative Metric

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