{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Freesurfer Hippocampal Subfields" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "SUBJECTS_DIR = '../tests/subjects'\n", "SUBJECT = 'bert'" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['lh.hippoSfVolumes-T1.v10.txt', 'lh.hippoSfVolumes-T1-T2.v10.txt']" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import os\n", "from freesurfer_volume_reader.freesurfer import HippocampalSubfieldsVolumeFile\n", "\n", "volume_files = list(filter(lambda f: f.subject == SUBJECT, \n", " HippocampalSubfieldsVolumeFile.find(SUBJECTS_DIR)))\n", "[os.path.basename(f.absolute_path) for f in volume_files]" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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subfieldvolume_mm^3subjecthemisphereT1_inputanalysis_id
0Hippocampal_tail123.456789bertleftTrueNone
1subiculum234.567891bertleftTrueNone
2CA134.567891bertleftTrueNone
3hippocampal-fissure345.678912bertleftTrueNone
4presubiculum456.789123bertleftTrueNone
\n", "
" ], "text/plain": [ " subfield volume_mm^3 subject hemisphere T1_input analysis_id\n", "0 Hippocampal_tail 123.456789 bert left True None\n", "1 subiculum 234.567891 bert left True None\n", "2 CA1 34.567891 bert left True None\n", "3 hippocampal-fissure 345.678912 bert left True None\n", "4 presubiculum 456.789123 bert left True None" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas\n", "volume_frame = pandas.concat([f.read_volumes_dataframe() for f in volume_files])\n", "volume_frame.head()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['CA1',\n", " 'CA3',\n", " 'CA4',\n", " 'GC-ML-DG',\n", " 'HATA',\n", " 'Hippocampal_tail',\n", " 'Whole_hippocampus',\n", " 'fimbria',\n", " 'hippocampal-fissure',\n", " 'molecular_layer_HP',\n", " 'parasubiculum',\n", " 'presubiculum',\n", " 'subiculum']" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted(volume_frame['subfield'].unique())" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[None, 'T2']" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list(volume_frame['analysis_id'].unique())" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "T1 13\n", "T1 & T2 13\n", "Name: segmentation_mode, dtype: int64" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def generate_mode_label(row):\n", " mri_sequences = ['T1' if row['T1_input'] else None,\n", " row['analysis_id'].split('_')[0] if row['analysis_id'] else None]\n", " return ' & '.join(filter(None, mri_sequences))\n", "\n", "volume_frame['segmentation_mode'] = volume_frame.apply(generate_mode_label, axis=1)\n", "volume_frame.to_csv('freesurfer_hipposf_volumes_{}.csv'.format(SUBJECT),\n", " index=False)\n", "volume_frame['segmentation_mode'].value_counts().sort_index()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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segmentation_modeT1T1 & T2
subfieldhemisphere
CA1left34.56789144.567891
CA3left678.912345678.912445
CA4left789.123456789.124456
GC-ML-DGleft567.891234567.891244
HATAleft91.23456791.244567
Hippocampal_tailleft123.456789124.456789
Whole_hippocampusleft1234.5678991244.567899
fimbrialeft89.12345689.124456
hippocampal-fissureleft345.678912445.678912
molecular_layer_HPleft56.78912356.789124
parasubiculumleft45.67891245.678912
presubiculumleft456.789123456.789124
subiculumleft234.567891244.567891
\n", "
" ], "text/plain": [ "segmentation_mode T1 T1 & T2\n", "subfield hemisphere \n", "CA1 left 34.567891 44.567891\n", "CA3 left 678.912345 678.912445\n", "CA4 left 789.123456 789.124456\n", "GC-ML-DG left 567.891234 567.891244\n", "HATA left 91.234567 91.244567\n", "Hippocampal_tail left 123.456789 124.456789\n", "Whole_hippocampus left 1234.567899 1244.567899\n", "fimbria left 89.123456 89.124456\n", "hippocampal-fissure left 345.678912 445.678912\n", "molecular_layer_HP left 56.789123 56.789124\n", "parasubiculum left 45.678912 45.678912\n", "presubiculum left 456.789123 456.789124\n", "subiculum left 234.567891 244.567891" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "volume_frame.pivot_table(values='volume_mm^3',\n", " index=['subfield', 'hemisphere'],\n", " columns='segmentation_mode')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", " $(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " if (mpl.ratio != 1) {\n", " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " fig.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " '
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');\n", " var button = $('');\n", " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", " buttongrp.append(button);\n", " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", " titlebar.prepend(buttongrp);\n", "}\n", "\n", "mpl.figure.prototype._root_extra_style = function(el){\n", " var fig = this\n", " el.on(\"remove\", function(){\n", "\tfig.close_ws(fig, {});\n", " });\n", "}\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(el){\n", " // this is important to make the div 'focusable\n", " el.attr('tabindex', 0)\n", " // reach out to IPython and tell the keyboard manager to turn it's self\n", " // off when our div gets focus\n", "\n", " // location in version 3\n", " if (IPython.notebook.keyboard_manager) {\n", " IPython.notebook.keyboard_manager.register_events(el);\n", " }\n", " else {\n", " // location in version 2\n", " IPython.keyboard_manager.register_events(el);\n", " }\n", "\n", "}\n", "\n", "mpl.figure.prototype._key_event_extra = function(event, name) {\n", " var manager = IPython.notebook.keyboard_manager;\n", " if (!manager)\n", " manager = IPython.keyboard_manager;\n", "\n", " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", " event.shiftKey = false;\n", " // Send a \"J\" for go to next cell\n", " event.which = 74;\n", " event.keyCode = 74;\n", " manager.command_mode();\n", " manager.handle_keydown(event);\n", " }\n", "}\n", "\n", "mpl.figure.prototype.handle_save = function(fig, msg) {\n", " fig.ondownload(fig, null);\n", "}\n", "\n", "\n", "mpl.find_output_cell = function(html_output) {\n", " // Return the cell and output element which can be found *uniquely* in the notebook.\n", " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", " // IPython event is triggered only after the cells have been serialised, which for\n", " // our purposes (turning an active figure into a static one), is too late.\n", " var cells = IPython.notebook.get_cells();\n", " var ncells = cells.length;\n", " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", " data = data.data;\n", " }\n", " if (data['text/html'] == html_output) {\n", " return [cell, data, j];\n", " }\n", " }\n", " }\n", " }\n", "}\n", "\n", "// Register the function which deals with the matplotlib target/channel.\n", "// The kernel may be null if the page has been refreshed.\n", "if (IPython.notebook.kernel != null) {\n", " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "subfield_volume_frame = volume_frame[volume_frame['subfield'] != 'Whole_hippocampus']\n", "\n", "pyplot.figure()\n", "seaborn.set(font_scale=0.8)\n", "ax = seaborn.barplot(data=subfield_volume_frame[subfield_volume_frame['hemisphere'] == 'left'],\n", " x='subfield',\n", " y='volume_mm^3',\n", " hue='segmentation_mode')\n", "ax.set_xticklabels(ax.get_xticklabels(), rotation=60)\n", "ax.set_title('Hippocampal Subfield Volumes of Subject {}\\nLeft Hemisphere'.format(SUBJECT));" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.10" } }, "nbformat": 4, "nbformat_minor": 2 }