{"id":2281,"date":"2011-11-08T15:05:00","date_gmt":"2011-11-08T20:05:00","guid":{"rendered":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/niral\/download\/download-documents\/"},"modified":"2024-02-05T11:29:23","modified_gmt":"2024-02-05T16:29:23","slug":"download-documents","status":"publish","type":"page","link":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/download\/download-documents\/","title":{"rendered":"Download Documents &amp; Tutorials"},"content":{"rendered":"<h2>Talks &amp; Tutorials<\/h2>\n<ul>\n<li>Using docker for Deep Learning on NIRAL servers:\n<ul>\n<li>Basic intro to docker, how to use NIRAL servers for Deep Learning, how to schedule the server etc [<a href=\"https:\/\/www.youtube.com\/watch?v=b_2g0pUzX-A\">Youtube video of tutorial<\/a>]<\/li>\n<\/ul>\n<\/li>\n<li>Python tutorials for beginners\n<ul>\n<li>Basic intro, how to use jupyter, loading, merging and saving csv files via dataframes in pandas: [<a href=\"https:\/\/youtu.be\/JoHUFq084XM\">Youtube video of tutorial<\/a>], [<a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2020\/05\/PythonJupyterTutorial.pptx\">PPT of tutorial<\/a>]<\/li>\n<\/ul>\n<\/li>\n<li>Diffusion MRI tutorial lessons as PPTX &amp; Videos:\n<ul>\n<li>Update 2022: infant diffusion MRI preprocessing: <a href=\"https:\/\/vimeo.com\/760105558\">Video at Fit&#8217;NG vimeo<\/a><\/li>\n<li>Basics of diffusion, tensors, tensor properties, visualization:\u00a0[<a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2019\/03\/DMRI_intro-Lession1.pptx\">DMRI_intro-Lession1<\/a>],\u00a0[<a href=\"https:\/\/www.youtube.com\/watch?v=yFZfXZqNAgY&amp;feature=youtu.be\">Lesson 1 at YouTube &#8211; Intro<\/a>]<\/li>\n<li>Tractography, analysis frameworks (regional, voxel\/TBSS, fiber tract based):\u00a0[<a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2019\/03\/DMRI_intro-Lession2.pptx\">DMRI_intro-Lession2<\/a>], [<a href=\"https:\/\/youtu.be\/h9BRvxBqdDo\">Lesson 2 at YouTube &#8211; Tracts<\/a>],<\/li>\n<li>Diffusion MRI QC with DTIPrep and FS 5.12\/6.1:\u00a0[<a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2019\/04\/DMRI_intro-Lession3-QC.pptx\">DMRI_intro-Lesion3-QC<\/a>], [<a href=\"https:\/\/www.youtube.com\/watch?v=IVQbwuhf3Ss&amp;feature\">Lesson 3 at YouTube &#8211; QC<\/a>]<\/li>\n<li>How to build DTI atlases with DTIAtlasBuilder:\u00a0[<a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2019\/04\/DMRI_intro-Lession4-AtlasFibersNProfiles_P1-2.pptx\">DMRI_intro-Lesson4-AtlasBuilder<\/a>], [<a href=\"https:\/\/www.youtube.com\/watch?v=1-qj_UWouso\">Lesson 4a at Youtube &#8211; Atlas Builder<\/a>]<\/li>\n<li>Automatic tractography via AutoTract, Fiber Profiles via DTIAtlasFiberAnalyzer and FADTTSter: [<a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2019\/06\/DMRI_intro-Lession4-AtlasFibersNProfiles_P2C.pptx\">DMRI_intro-Lesson4b-TractAnalysis]<\/a> <a href=\"https:\/\/www.youtube.com\/watch?v=aFhJTboav5E&amp;t=3s\">[Lesson 4b on Youtube &#8211; Fiber analysis]<\/a><\/li>\n<li>Higher-order\u00a0models of diffusion, Diffusion structural connectivity: <a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2019\/07\/DMRI_intro-Lession5-HigherThanDTI.pptx\">[DTI_intro-Lesson5-HigherOrderModels]<\/a> <a href=\"https:\/\/www.youtube.com\/watch?v=XUOxQ0sp4qg\">[Lesson 5 on Youtube &#8211; Fiber analysis]<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h2>Laboratory manual ACE-IBIS Infant Study Image processing pipelines [ <a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2018\/07\/ACE-IBIS-NeuroImageAnalysis-Lab-Manual-feb2012_final.pdf\">pdf link<\/a> ]<\/h2>\n<ul>\n<li>Image processing methods and pipelines<\/li>\n<li>Guidelines for segmentation of anatomical structures<\/li>\n<li>Geometric phantom calibration of structural MRI<\/li>\n<\/ul>\n<h2>Rhesus Monkey Brain Atlas: Subcortical Gray Structures <a title=\"\" href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2018\/07\/rhesusmonkeybrainatlassubcorticalgraystructures.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">[pdf]<\/a> (Manual Tracing for Hippocampus, Amygdala, Caudate, and Putamen)<\/h2>\n<ul>\n<li>Tracing is done in a combination of the three orthogonal planes, as specified in the<br \/>\ndetailed methods that follow.<\/li>\n<li>Each region of interest was originally defined in the right hemisphere. The labels<br \/>\nwere then reflected onto the left hemisphere and all borders checked and adjusted<br \/>\nmanually when necessary.<\/li>\n<li>For the initial parcellation, the user used the \u201cpaint over function\u201d of IRIS\/SNAP on<br \/>\nthe T1 template of the atlas.<\/li>\n<\/ul>\n<h2>Regional and Lobe Parcellation Rhesus Monkey Brain Atlas <a title=\"\" href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2018\/07\/regionallobeparcellationrhesusmonkeybrainatlas.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">[pdf]<\/a> (Manual Tracing for Parcellation Template)<\/h2>\n<ul>\n<li>Traces are performed in a systematic order they, allowing the more easily defined<br \/>\nregions to provide borders for the more difficult regions<\/li>\n<li>Many parts of the protocol instruct the user to trace to or from the \u201cdepth\u201d of a sulcus.<br \/>\nThe \u201cdepth\u201d of a sulcus refers to the gray matter\/white matter border within the<br \/>\nsulcus.<\/li>\n<li>Tracing is done in a combination of the three orthogonal planes, as specified in the<br \/>\ndetailed methods that follow.<\/li>\n<li>Each region of interest was originally defined in the right hemisphere. The labels<br \/>\nwere then reflected onto the left hemisphere and all borders checked and adjusted<br \/>\nmanually when necessary.<\/li>\n<li>For the initial parcellation, the user used the \u201cpaint over function\u201d of IRIS\/SNAP<br \/>\npainting over label 1 and label 2 (GM and WM) of the hard tissue segmentation. The<br \/>\nresulting labels were then dilated to fill the entire brain space.<\/li>\n<\/ul>\n<div>\n<h2>Structural MRI Quality Control Manual <a title=\"\" href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2018\/07\/structural-mri-visual-qc.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">[pdf]<\/a><\/h2>\n<ul>\n<li>This document provides information about how structural MRI T1w and T2w data is scored for its quality with respect to the presence of artifacts etc.<\/li>\n<\/ul>\n<\/div>\n<h2>Infant Multi-Atlas Hippocampus and Amygdala Segmentation Information\u00a0<a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-content\/uploads\/sites\/770\/2018\/10\/HippoAmySeg_BasicFormat.pdf\">[pdf]<\/a><\/h2>\n<ul>\n<li>This document discusses the AutoSeg based multi-atlas hippocampus and amygdala segmentation, followed by manual correction of the automatic segmentation.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Talks &amp; Tutorials Using docker for Deep Learning on NIRAL servers: Basic intro to docker, how to use NIRAL servers for Deep Learning, how to schedule the server etc [Youtube video of tutorial] Python tutorials for beginners Basic intro, how to use jupyter, loading, merging and saving csv files via dataframes in pandas: [Youtube video &hellip; <a href=\"https:\/\/www.med.unc.edu\/psych\/research\/niral\/download\/download-documents\/\" aria-label=\"Read more about Download Documents &amp; Tutorials\">Read more<\/a><\/p>\n","protected":false},"author":7371,"featured_media":0,"parent":2231,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-2281","page","type-page","status-publish","hentry","odd"],"acf":[],"_links_to":[],"_links_to_target":[],"_links":{"self":[{"href":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-json\/wp\/v2\/pages\/2281","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-json\/wp\/v2\/users\/7371"}],"replies":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-json\/wp\/v2\/comments?post=2281"}],"version-history":[{"count":0,"href":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-json\/wp\/v2\/pages\/2281\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-json\/wp\/v2\/pages\/2231"}],"wp:attachment":[{"href":"https:\/\/www.med.unc.edu\/psych\/research\/niral\/wp-json\/wp\/v2\/media?parent=2281"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}