29:null 2a:["$","title",null,{"children":"The NorCOAST Imaging Dataset | landge | Observable"}] 2f:T426,Object.assign( Plot.plot({ height: 15000, width: 500, caption: "", marginTop: 40, marginRight: 20, marginLeft: 100, marginBottom: 30, padding: 0, color: { scheme: "YlGnBu" }, style: { "font-size": 10, fontstroke: "#91bfdb", maxWidth: "20000px" }, x: { type: "band", label: "Imaging at timepoint available", paddingInner: 0.1, domain: [ "ses-clinical", "ses-study-MR", "18-mon-follow-up", "36-mon-follow-up" ] }, y: { type: "band", padding: 0.15, label: "All NorCOAST subjects" }, marks: [ Plot.cell(timepoinst_data, { x: "timepoint", y: "subject-id", fill: "count" }), Plot.text(timepoinst_data, { x: "timepoint", y: "subject-id", text: "timepoint" }), Plot.gridX({ stroke: "#0868a3" }), Plot.gridY({ stroke: "#0868a3" }) ] }), { style: `max-width: ${width}px; overflow: scroll; max-height: 700px; overflow-y: scroll` } )30:T426,Object.assign( Plot.plot({ height: 15000, width: 500, caption: "", marginTop: 40, marginRight: 20, marginLeft: 100, marginBottom: 30, padding: 0, color: { scheme: "YlGnBu" }, style: { "font-size": 10, fontstroke: "#91bfdb", maxWidth: "20000px" }, x: { type: "band", label: "Imaging at timepoint available", paddingInner: 0.1, domain: [ "ses-clinical", "ses-study-MR", "18-mon-follow-up", "36-mon-follow-up" ] }, y: { type: "band", padding: 0.15, label: "All NorCOAST subjects" }, marks: [ Plot.cell(timepoinst_data, { x: "timepoint", y: "subject-id", fill: "count" }), Plot.text(timepoinst_data, { x: "timepoint", y: "subject-id", text: "timepoint" }), Plot.gridX({ stroke: "#0868a3" }), Plot.gridY({ stroke: "#0868a3" }) ] }), { style: `max-width: ${width}px; overflow: scroll; max-height: 700px; overflow-y: scroll` } )31:T4e6,Object.assign( Plot.plot({ height: 15000, caption: "", width: 2000, marginTop: 40, marginRight: 20, marginLeft: 100, marginBottom: 30, padding: 0, color: { scheme: "YlGnBu" }, style: { "font-size": 10, fontstroke: "#91bfdb", maxWidth: "20000px" }, x: { type: "band", label: "Available Imaging Data", paddingInner: 0.1, domain: [ "CT-1", "CT-2", "CTA", "DWI", "ADC", "3D-T1", "3D-FLAIR", "T1", "T2", "T2-FLAIR" ] }, fx: { domain: [ "ses-clinical", "ses-study-MR", "18-mon-follow-up", "36-mon-follow-up" ] }, facet: { data: summary, x: "timepoint" }, y: { type: "band", padding: 0.15, label: "All NorCOAST subjects" }, marks: [ Plot.cell(summary, { x: "modality", y: "subject-id", fill: "count" }), Plot.text(summary, { x: "modality", y: "subject-id", text: "modality" }), Plot.gridX({ stroke: "#0868a3" }), Plot.gridY({ stroke: "#0868a3" }) ] }), { style: `max-width: ${width}px; overflow: scroll; max-height: 700px; overflow-y: scroll` } )32:T97b,slide_style = html``33:[{"id":"1863dbddf59de5e99ccc4088c7bccfebb758facd5a024704e69dc2550ef70d9a008459c17b6b16f4caee7591b6754115cc3bed9069d05501e16a325e1aebf227","href":"https://static.observableusercontent.com/files/1863dbddf59de5e99ccc4088c7bccfebb758facd5a024704e69dc2550ef70d9a008459c17b6b16f4caee7591b6754115cc3bed9069d05501e16a325e1aebf227","name":"landge_infographic_chart_include_gold_silver_and_bronze_data_vi_d8b4e7e6-51da-45e7-b722-f76d39807adf.png","type":"image/png","lastModified":1686059632865.905,"size":2001721},{"id":"77aff238750a41c77e349f80b9c818cd44178523dc191f6bced932d23426b2503f72fd3bddbec2cde14f9e03c28c252f6135449131ab4d12b83c57edce308cb1","href":"https://static.observableusercontent.com/files/77aff238750a41c77e349f80b9c818cd44178523dc191f6bced932d23426b2503f72fd3bddbec2cde14f9e03c28c252f6135449131ab4d12b83c57edce308cb1","name":"info_square.png","type":"image/png","lastModified":1686059891009.423,"size":1471192},{"id":"c9e4a75cdfa0924ea5faa57e54d2f4e821661cd8ecdd2b9a2985c6a8942e7631fa48142d1b4e023d0564cb49ac3244b37cb16359bb2b8656ef9d25d1a29546a5","href":"https://static.observableusercontent.com/files/c9e4a75cdfa0924ea5faa57e54d2f4e821661cd8ecdd2b9a2985c6a8942e7631fa48142d1b4e023d0564cb49ac3244b37cb16359bb2b8656ef9d25d1a29546a5","name":"Till_Schellhorn_profil.png","type":"image/png","lastModified":1686052454357.541,"size":9565131},{"id":"d4f2a53ce31173bb4c2d815807f94ebb828127b5beba16bede6ff94746be5a128537d9a2e0bb4659d9ab2e29cabc816d57f7b353fb6a0a8265f832df7320d591","href":"https://static.observableusercontent.com/files/d4f2a53ce31173bb4c2d815807f94ebb828127b5beba16bede6ff94746be5a128537d9a2e0bb4659d9ab2e29cabc816d57f7b353fb6a0a8265f832df7320d591","name":"landge_brain_affected_by_vascular_disease_and_neurodegnertion_i_a846dc9e-8232-48ae-aa69-9a194c90836f.png","type":"image/png","lastModified":1685997576807.905,"size":1820397}] 2d:{"id":"21642b1c3403272c","slug":null,"title":"The NorCOAST Imaging Dataset","thumbnail":"4307ceaf86f80611ce06a4b186e3e6c08816403ce593b001cbf7dece7687ed22","access_level":"public","create_time":"$D2023-06-05T19:23:59.214Z","update_time":"$D2024-05-28T08:40:59.126Z","view_time":null,"first_public_time":"$D2023-06-05T19:23:59.214Z","fork":false,"stars":1,"starred":false,"owner":{"type":"team","id":"9a982be031e511a9","login":"landge","name":"landge","avatar_url":"https://avatars-next.observableusercontent.com/6f2914ea305a7fab24656b3f566450833b123ea4c605da0d9f5ec5ada24946a3","tier":"starter_2024"},"version":495,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"0e1d4de604b77517","login":"landge","name":"landge","avatar_url":"https://avatars-next.observableusercontent.com/6f2914ea305a7fab24656b3f566450833b123ea4c605da0d9f5ec5ada24946a3","tier":null}],"members":[{"type":"individual","id":"0e1d4de604b77517","login":"landge","name":"landge","avatar_url":"https://avatars-next.observableusercontent.com/6f2914ea305a7fab24656b3f566450833b123ea4c605da0d9f5ec5ada24946a3","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"The NorCOAST Imaging Dataset","cells":[{"id":101,"value":"\n\n

\n

\n

The NorCOAST Imaging Dataset

\nTill Schellhorn, MD
\nPhD, PostDoc

\n\n

\nStavern
\n June, 7th
\n

\n\n

\n \n

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":157,"value":"# Total number of examinations (series)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":159,"value":"The total number of examinations is higher than the maximum number of participants for some sequences/modalities. In the case of DWI there are more than 1000 accquisitions because there are multiple volumes per examination.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":120,"value":"Plot.plot({\n height: 100,\n width: 1200,\n color: { scheme: \"YlGnBu\" },\n x: {\n type: \"band\",\n label: \"Available Imaging Data\",\n paddingInner: 0.1,\n domain: [\n \"CT-1\",\n \"CT-2\",\n \"CTA\",\n \"DWI\",\n \"ADC\",\n \"3D-T1\",\n \"3D-FLAIR\",\n \"T1\",\n \"T2\",\n \"T2-FLAIR\"\n ]\n },\n marks: [\n Plot.cell(data, Plot.groupX({ fill: \"count\" }, { x: \"modality\" })),\n Plot.text(\n data,\n Plot.groupX(\n { text: \"count\" },\n { x: \"modality\" },\n { fill: \"#fff\", strokewidth: 5 }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":305,"value":"# Number of examinations per timepoint","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":307,"value":"Sum of all examinations per timepoint regardless of modality. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":210,"value":"total_numbers = Plot.plot({\n width: 1000,\n marginLeft: 120,\n color: { scheme: \"YlGnBu\" },\n y: {\n grid: true,\n domain: [\n \"36-mon-follow-up\",\n \"18-mon-follow-up\",\n \"ses-study-MR\",\n \"ses-clinical\"\n ]\n },\n marks: [\n Plot.barX(\n data,\n Plot.groupY({ x: \"count\", fill: \"count\" }, { y: \"timepoint\" })\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":324,"value":"We collected a large number of study MRIs and clinical scans.\n___","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":319,"value":"## Number of examinations per modality","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":302,"value":"Plot.plot({\n width: 1000,\n marginLeft: 120,\n color: { scheme: \"YlGnBu\" },\n y: {\n grid: true,\n domain: [\n \"CT-1\",\n \"CT-2\",\n \"CTA\",\n \"DWI\",\n \"ADC\",\n \"3D-T1\",\n \"3D-FLAIR\",\n \"T1\",\n \"T2\",\n \"T2-FLAIR\"\n ]\n },\n marks: [\n Plot.barX(\n data,\n Plot.groupY({ x: \"count\", fill: \"count\" }, { y: \"modality\" })\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":328,"value":"___","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":180,"value":"## Number of examinations per timepoint and modality","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":183,"value":"- ses-clinical = Clinical imaging at time of stroke\n- ses-study-MR = Study MRI protocol during the first ten days after stroke\n- 18-mon-follow-up = Study MRI protocol at 18 month after stroke\n- 36-mon-follow-up = Study MRI protocol at 36 month after stroke\n\n____","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":189,"value":"Plot.plot({\n height: 450,\n width: 1000,\n marginLeft: 150,\n color: { scheme: \"YlGnBu\" },\n fy: {\n domain: [\n \"36-mon-follow-up\",\n \"18-mon-follow-up\",\n \"ses-study-MR\",\n \"ses-clinical\"\n ]\n },\n x: {\n type: \"band\",\n label: \"Available Imaging Data\",\n paddingInner: 0.1,\n domain: [\n \"CT-1\",\n \"CT-2\",\n \"CTA\",\n \"DWI\",\n \"ADC\",\n \"3D-T1\",\n \"3D-FLAIR\",\n \"T1\",\n \"T2\",\n \"T2-FLAIR\"\n ]\n },\n facet: {\n y: \"timepoint\",\n data: data\n },\n marks: [\n Plot.cell(data, Plot.groupX({ fill: \"count\" }, { x: \"modality\" })),\n Plot.text(data, Plot.groupX({ text: \"count\" }, { x: \"modality\" }))\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":393,"value":"# Imaging per timepoint","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":403,"value":"Imaging available per timepoint and participant.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":350,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":408,"value":"$30","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":345,"value":"# Every examination per subject and timepoint","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":347,"value":"Stacked timepoints on x-axis. Subjects on y-axis. Colors indicate multiple instances or accquisitions of same examination.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":330,"value":"$31","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":377,"value":"summary = aq_bas.groupby(\"subject-id\", \"timepoint\", \"modality\").rollup({\n count: op.count(\"modality\")\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":388,"value":"timepoinst_data\n .groupby(\"subject-id\")\n .rollup({\n count: op.count(\"subject-id\")\n })\n .view()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":337,"value":"timepoinst_data = aq_bas.groupby(\"subject-id\", \"timepoint\").rollup({\n count: op.count(\"timepoint\")\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":386,"value":"timepoinst_data1 = aq_bas\n .groupby(\"subject-id\", \"timepoint\")\n .rollup({\n count: op.count(\"timepoint\")\n })\n .view()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":429,"value":"Object.assign(\n Plot.plot({\n height: 15000,\n width: 200,\n caption: \"\",\n marginTop: 40,\n marginRight: 20,\n marginLeft: 100,\n marginBottom: 30,\n padding: 0,\n color: { scheme: \"YlGnBu\" },\n style: { \"font-size\": 10, fontstroke: \"#91bfdb\", maxWidth: \"20000px\" },\n marks: [\n Plot.dot(unique_timepoints_per_subject, {\n x: \"timepoint\",\n y: \"subject-id\"\n })\n ]\n }),\n {\n style: `max-width: ${width}px; overflow: scroll; max-height: 700px; overflow-y: scroll`\n }\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":456,"value":"unique_timepoints_per_subject = lodash.uniqWith(unique_input, lodash.isEqual)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":462,"value":"unique_input = data.map((d) => ({\n \"subject-id\": d[\"subject-id\"],\n timepoint: d.timepoint\n}))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":459,"value":"lodash = require(\"lodash\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":435,"value":"sub_time = data.map((d) => ({\n subject_id: d[\"subject-id\"],\n timepoint: d.timepoint\n}))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":335,"value":"aq_bas = aq.from(data)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":332,"value":"import { aq, op } from \"@uwdata/arquero\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":162,"value":"viewof table = Inputs.table(data, {})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":98,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":117,"value":"data = d3.csv(\n \"https://raw.githubusercontent.com/landge/NorCOAST_Imaging_Dataset/master/code/deleted_duplicate_files.csv?token=GHSAT0AAAAAACS4BQ5TLHJHSJJXSG3YUIJYZSVU2OA\"\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":418,"value":"bianca_filtered = aq_bianca.filter((d) =>\n op.startswith(d[\"subject-id\"], \"sub-\")\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":416,"value":"aq_bianca = aq.from(bianca)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":412,"value":"bianca = d3.csv(\n \"https://raw.githubusercontent.com/landge/NorCOAST_Imaging_Dataset/master/code/freesurfer_and_bianca_results.csv?token=GHSAT0AAAAAACS4BQ5SZX6M5GMFUGIA45DKZSVUZHQ\"\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":487,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 2e:"$2d:body"