<?xml version="1.0" encoding="utf-8"?>
<phantom>
<phantomType>MagphanEMR051</phantomType>
<fallbackCentroidCNR distance="1.756220" />
<snr>49.671512</snr>
<cnr>58.072462 39.963126 25.494787 35.482979</cnr>
<maxDimming>0.020491</maxDimming>
<scale>1.008776 1.006208 1.002673</scale>
<nonlinear>0.710116 0.460693 0.569871</nonlinear>
<landmarkList coordinates="physical" space="RAS" count="165">
	<landmark>
		<name>SNR</name>
		<expected>-3.027123 30.735095 11.526837</expected>
		<detected>-2.043655 30.071085 12.782928</detected>
		<isPrecise>no</isPrecise>
		<fitResidual>1.728772</fitResidual>
	</landmark>
	<landmark>
		<name>15mm@90mm</name>
		<expected>85.851900 28.901026 16.680998</expected>
		<detected>86.310946 29.378059 16.654620</detected>
		<isPrecise>no</isPrecise>
		<fitResidual>0.723124</fitResidual>
	</landmark>
	<landmark>
		<name>15mm@60mm</name>
		<expected>0.433230 25.864665 -48.245354</expected>
		<detected>0.095465 26.191916 -48.666488</detected>
		<isPrecise>no</isPrecise>
		<fitResidual>0.483855</fitResidual>
	</landmark>
	<landmark>
		<name>CNR-Orange</name>
		<expected>56.670384 51.440266 14.266094</expected>
		<detected>56.952907 51.567248 13.524743</detected>
		<isPrecise>no</isPrecise>
		<fitResidual>1.037122</fitResidual>
	</landmark>
	<landmark>
		<name>CNR-Red</name>
		<expected>-63.127154 50.005449 7.447645</expected>
		<detected>-63.112619 49.931690 7.423397</detected>
		<isPrecise>no</isPrecise>
		<fitResidual>0.620705</fitResidual>
	</landmark>
	<landmark>
		<name>CNR-Yellow</name>
		<expected>-62.724630 10.029924 8.787580</expected>
		<detected>-63.086875 8.652456 8.986648</detected>
		<isPrecise>no</isPrecise>
		<fitResidual>1.358718</fitResidual>
	</landmark>
	<landmark>
		<name>CNR-Green</name>
		<expected>57.072907 11.464741 15.606029</expected>
		<detected>57.355891 10.222358 15.236077</detected>
		<isPrecise>no</isPrecise>
		<fitResidual>1.294573</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_23</name>
		<expected>-34.692093 31.362493 39.756893</expected>
		<detected>-34.422304 31.651540 39.732420</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.498007</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_24</name>
		<expected>-31.260922 29.390288 -20.112443</expected>
		<detected>-31.606403 29.710548 -20.159085</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.377099</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_25</name>
		<expected>25.206676 32.079902 43.166118</expected>
		<detected>25.355602 32.660566 43.268876</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.607641</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_26</name>
		<expected>28.637846 30.107697 -16.703219</expected>
		<detected>28.267725 29.892687 -16.673289</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.559097</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_01</name>
		<expected>-5.012678 2.068255 52.444680</expected>
		<detected>-5.156785 1.708012 52.413490</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.381987</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_02</name>
		<expected>-0.437784 -0.561351 -27.381103</expected>
		<detected>-0.529416 -0.935811 -27.511817</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.160297</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_13</name>
		<expected>35.754761 60.788613 27.792184</expected>
		<detected>35.679743 61.016210 28.049884</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.454508</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_14</name>
		<expected>37.470346 59.802510 -2.142484</expected>
		<detected>37.677656 59.755213 -1.808424</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.291409</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_15</name>
		<expected>-44.110264 59.832068 23.246552</expected>
		<detected>-44.161136 59.910588 22.902315</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.362760</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_16</name>
		<expected>-42.394679 58.845966 -6.688116</expected>
		<detected>-43.275610 59.233641 -7.066021</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.547320</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_15</name>
		<expected>25.508569 2.098258 44.171069</expected>
		<detected>25.530583 1.708384 44.669871</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.508731</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_16</name>
		<expected>28.939739 0.126054 -15.698268</expected>
		<detected>28.556268 -0.195555 -15.385939</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.630661</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_17</name>
		<expected>-34.390200 1.380850 40.761845</expected>
		<detected>-37.219157 0.287337 43.506674</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>3.995594</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_18</name>
		<expected>-30.959030 -0.591355 -19.107492</expected>
		<detected>-31.319857 -0.821118 -18.904762</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.434888</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_01</name>
		<expected>9.081356 61.475795 56.306343</expected>
		<detected>8.992165 61.754986 56.266167</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.435736</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_04</name>
		<expected>14.228111 58.517488 -33.497662</expected>
		<detected>13.846954 58.034675 -33.236973</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.780332</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_07</name>
		<expected>-20.868029 61.117090 54.601731</expected>
		<detected>-20.254509 61.546656 54.439724</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.683749</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_10</name>
		<expected>-15.721273 58.158783 -35.202275</expected>
		<detected>-15.386411 58.028017 -35.222661</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.705368</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_27</name>
		<expected>-6.458293 32.707300 71.396174</expected>
		<detected>-5.818516 33.337530 71.366158</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.755337</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_01</name>
		<expected>10.495048 90.471336 25.366723</expected>
		<detected>10.840461 91.175018 25.074491</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.572116</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_02</name>
		<expected>12.210634 89.485233 -4.567946</expected>
		<detected>11.773624 89.714946 -4.108099</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.647973</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_03</name>
		<expected>-19.454336 90.112631 23.662111</expected>
		<detected>-19.789836 89.895409 23.014740</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.916757</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_04</name>
		<expected>-17.738751 89.126529 -6.272558</expected>
		<detected>-17.693332 89.470366 -5.826990</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.584156</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_01</name>
		<expected>11.693561 -28.555788 29.356380</expected>
		<detected>11.659790 -28.925633 29.656213</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.325583</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_02</name>
		<expected>13.409146 -29.541890 -0.578288</expected>
		<detected>13.460509 -30.381351 -1.553240</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.072422</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_03</name>
		<expected>-18.255823 -28.914492 27.651768</expected>
		<detected>-17.688379 -29.119128 27.783870</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.660289</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_04</name>
		<expected>-16.540238 -29.900595 -2.282900</expected>
		<detected>-16.827970 -30.206321 -2.126600</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.332295</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_05</name>
		<expected>-6.156401 2.725656 72.401125</expected>
		<detected>-5.569256 2.812901 72.750489</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.474875</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_06</name>
		<expected>0.705939 -1.218753 -47.337548</expected>
		<detected>0.276339 -1.317238 -46.815154</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.760893</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_15</name>
		<expected>-36.407678 32.348595 69.691562</expected>
		<detected>-36.093617 33.194209 69.648314</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.875946</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_16</name>
		<expected>-29.545337 28.404186 -50.047112</expected>
		<detected>-29.388620 28.032769 -50.067391</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.751365</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_17</name>
		<expected>23.491091 33.066004 73.100786</expected>
		<detected>23.164830 33.570658 73.130047</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.947354</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_18</name>
		<expected>30.353432 29.121595 -46.637888</expected>
		<detected>30.174352 29.301492 -46.457042</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.397478</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_19</name>
		<expected>-64.641477 31.003789 38.052281</expected>
		<detected>-65.083591 31.574949 37.876940</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.533996</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_20</name>
		<expected>-61.210307 29.031584 -21.817056</expected>
		<detected>-61.286490 28.629135 -26.145313</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>4.034967</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_21</name>
		<expected>55.156061 32.438606 44.870730</expected>
		<detected>54.895985 32.836611 44.898052</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.005051</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_22</name>
		<expected>58.587231 30.466401 -14.998607</expected>
		<detected>59.026546 30.566852 -14.544707</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.308609</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_17</name>
		<expected>39.030740 61.834499 58.010955</expected>
		<detected>39.568674 61.998276 57.919535</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.433996</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_18</name>
		<expected>44.177496 58.876192 -31.793050</expected>
		<detected>44.501191 59.099757 -31.405480</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.333721</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_19</name>
		<expected>-50.817413 60.758386 52.897118</expected>
		<detected>-53.806140 60.522258 54.337964</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>3.155653</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_20</name>
		<expected>-45.670658 57.800079 -36.906887</expected>
		<detected>-45.915818 57.771186 -36.989371</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.422609</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_02</name>
		<expected>7.937632 62.133196 76.262788</expected>
		<detected>8.468421 61.932197 75.438304</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.190351</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_05</name>
		<expected>15.371835 57.860086 -53.454108</expected>
		<detected>15.597863 57.791382 -53.703514</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.408658</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_08</name>
		<expected>-22.011752 61.774492 74.558176</expected>
		<detected>-21.928318 61.764847 74.519732</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.302651</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_11</name>
		<expected>-14.577550 57.501382 -55.158720</expected>
		<detected>-13.310817 58.357584 -55.329051</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.779694</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_11</name>
		<expected>23.792983 3.084361 74.105737</expected>
		<detected>23.365619 3.040517 73.709646</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.133667</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_12</name>
		<expected>30.655324 -0.860049 -45.632936</expected>
		<detected>30.552906 -1.014895 -45.343241</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.394150</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_13</name>
		<expected>-36.105785 2.366952 70.696513</expected>
		<detected>-35.783229 2.644718 71.083267</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.654878</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_14</name>
		<expected>-29.243445 -1.577457 -49.042160</expected>
		<detected>-29.180658 -1.963169 -49.052608</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.610581</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_19</name>
		<expected>55.457953 2.456963 45.875681</expected>
		<detected>54.889645 2.543109 45.611065</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.361427</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_20</name>
		<expected>58.889123 0.484758 -13.993655</expected>
		<detected>59.159469 0.010903 -13.581556</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.388807</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_21</name>
		<expected>-64.339585 1.022146 39.057233</expected>
		<detected>-64.661368 1.172939 39.309980</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.540198</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_22</name>
		<expected>-60.908415 -0.950059 -20.812104</expected>
		<detected>-63.807810 -1.266371 -24.587531</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>4.118747</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_05</name>
		<expected>8.779463 91.457438 55.301391</expected>
		<detected>7.074847 90.400021 56.027358</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>2.490716</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_06</name>
		<expected>13.926219 88.499131 -34.502614</expected>
		<detected>13.718301 88.201463 -34.018523</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.830806</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_07</name>
		<expected>-21.169921 91.098734 53.596779</expected>
		<detected>-21.617792 91.288563 52.937228</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.897332</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_08</name>
		<expected>-16.023166 88.140427 -36.207226</expected>
		<detected>-16.754324 87.829069 -35.784515</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.973649</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_13</name>
		<expected>40.444433 90.830040 27.071335</expected>
		<detected>40.455992 91.159886 26.802682</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.666521</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_14</name>
		<expected>42.160018 89.843938 -2.863333</expected>
		<detected>42.515697 89.956754 -2.348472</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.411894</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_15</name>
		<expected>-49.403720 89.753927 21.957499</expected>
		<detected>-50.466604 89.775163 22.163565</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.858221</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_16</name>
		<expected>-47.688135 88.767825 -7.977170</expected>
		<detected>-48.489396 89.117445 -7.672979</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.617632</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_05</name>
		<expected>9.977976 -27.569686 59.291049</expected>
		<detected>9.436583 -28.132476 59.565865</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.884366</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_06</name>
		<expected>15.124732 -30.527993 -30.512956</expected>
		<detected>15.754225 -30.903204 -29.814425</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.005333</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_07</name>
		<expected>-19.971408 -27.928390 57.586437</expected>
		<detected>-19.698018 -28.141466 57.723402</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.271794</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_08</name>
		<expected>-14.824653 -30.886697 -32.217569</expected>
		<detected>-14.812015 -31.922863 -31.998438</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.813648</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_13</name>
		<expected>41.642946 -28.197084 31.060992</expected>
		<detected>42.180473 -28.509830 30.544416</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.734770</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_14</name>
		<expected>43.358531 -29.183186 1.126324</expected>
		<detected>44.281975 -29.177192 0.968637</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.743067</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_15</name>
		<expected>-48.205208 -29.273197 25.947156</expected>
		<detected>-48.428711 -29.269767 25.994655</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.429198</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_16</name>
		<expected>-46.489622 -30.259299 -3.987512</expected>
		<detected>-46.472019 -30.543540 -3.736777</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.674537</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_25</name>
		<expected>63.644595 59.109350 -30.685052</expected>
		<detected>63.815032 59.124230 -30.002046</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.572107</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_26</name>
		<expected>-70.284513 60.525228 51.789121</expected>
		<detected>-72.558888 60.707827 52.409798</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>2.009143</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_21</name>
		<expected>37.887017 62.491901 77.967400</expected>
		<detected>37.464687 62.937582 77.472854</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.363385</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_22</name>
		<expected>-44.526934 57.142678 -56.863332</expected>
		<detected>-43.834747 57.252407 -56.498187</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.499334</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_09</name>
		<expected>-3.918712 119.280882 8.558880</expected>
		<detected>-3.565660 119.592258 8.976954</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.598288</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_09</name>
		<expected>-2.126477 -58.710141 14.524942</expected>
		<detected>-2.475726 -58.820837 15.061942</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.828060</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_01</name>
		<expected>22.787626 113.353888 38.646457</expected>
		<detected>23.024434 113.673993 38.664530</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.310754</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_02</name>
		<expected>26.024363 111.493442 -17.830284</expected>
		<detected>26.027104 111.572505 -17.193894</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.693630</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_03</name>
		<expected>-33.716879 112.677133 35.430422</expected>
		<detected>-34.188244 112.545294 35.280935</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.740972</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_04</name>
		<expected>-30.480142 110.816686 -21.046319</expected>
		<detected>-31.435478 110.516457 -20.628288</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.142471</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_05</name>
		<expected>-5.334278 118.703490 33.551335</expected>
		<detected>-3.288227 123.794389 34.251741</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>4.985053</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_06</name>
		<expected>-2.474969 117.059986 -16.339779</expected>
		<detected>-3.023316 117.177297 -16.210781</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.608465</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_07</name>
		<expected>21.053197 118.180658 10.026288</expected>
		<detected>20.887540 118.042349 9.954968</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.789097</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3b_08</name>
		<expected>-28.862444 117.582818 7.185268</expected>
		<detected>-29.710862 117.788877 7.565184</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.818683</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_17</name>
		<expected>42.211016 91.982002 60.908181</expected>
		<detected>42.348706 91.856957 60.495972</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.035749</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_18</name>
		<expected>47.780949 88.780456 -36.279709</expected>
		<detected>47.483120 89.153932 -35.577248</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.798272</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_19</name>
		<expected>-55.024652 90.817408 55.373874</expected>
		<detected>-56.102304 89.754278 55.400462</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.683056</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_20</name>
		<expected>-49.454719 87.615863 -41.814016</expected>
		<detected>-50.413312 87.678738 -41.160374</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.076368</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_09</name>
		<expected>7.504212 92.190441 77.552828</expected>
		<detected>7.138096 91.417067 77.165150</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.535037</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_10</name>
		<expected>15.201470 87.766128 -56.754051</expected>
		<detected>14.303591 87.714867 -56.278971</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.029931</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_11</name>
		<expected>-22.445173 91.831736 75.848216</expected>
		<detected>-22.197592 91.843668 75.599998</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.606275</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_12</name>
		<expected>-14.747914 87.407424 -58.458663</expected>
		<detected>-15.044816 87.451234 -58.020369</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.728246</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_21</name>
		<expected>62.706809 91.096677 28.338430</expected>
		<detected>66.170327 95.516393 29.999744</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>5.129326</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_22</name>
		<expected>64.422394 90.110574 -1.596238</expected>
		<detected>68.601558 93.818710 -3.342291</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>5.383127</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_23</name>
		<expected>-71.666096 89.487290 20.690404</expected>
		<detected>-72.808683 89.665994 20.611746</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.644013</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2b_24</name>
		<expected>-69.950511 88.501188 -9.244265</expected>
		<detected>-70.759377 88.968449 -9.084301</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.504236</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_03</name>
		<expected>6.782472 62.797172 96.418798</expected>
		<detected>6.550317 63.321601 96.154427</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.903846</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_06</name>
		<expected>16.526995 57.196111 -73.610118</expected>
		<detected>20.697336 59.165045 -75.453486</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>5.010011</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_09</name>
		<expected>-23.166913 62.438468 94.714186</expected>
		<detected>-22.357027 63.136734 94.310792</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.999329</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_12</name>
		<expected>-13.422389 56.837406 -75.314730</expected>
		<detected>-13.222965 54.418793 -80.929964</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>5.926113</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_29</name>
		<expected>80.878500 61.329060 30.360467</expected>
		<detected>80.992996 61.475760 30.234529</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.854475</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_30</name>
		<expected>82.594086 60.342958 0.425798</expected>
		<detected>83.094200 59.962899 0.562597</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.596689</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_31</name>
		<expected>-89.234003 59.291620 20.678270</expected>
		<detected>-89.594526 59.717960 20.547373</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.436046</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_32</name>
		<expected>-87.518418 58.305518 -9.256399</expected>
		<detected>-88.888808 57.978127 -9.186374</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.907341</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_23</name>
		<expected>45.830176 57.926247 -60.630114</expected>
		<detected>44.807187 57.827665 -59.948149</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.352107</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_24</name>
		<expected>-52.470093 61.708331 81.734182</expected>
		<detected>-51.266079 61.905548 81.087742</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.516349</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_27</name>
		<expected>67.881981 62.180051 59.653065</expected>
		<detected>68.362349 62.046346 59.810313</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.540650</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1b_28</name>
		<expected>-74.521898 57.454527 -38.548996</expected>
		<detected>-74.822577 57.659093 -38.818411</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.524053</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_23</name>
		<expected>54.683495 3.487892 76.864992</expected>
		<detected>54.118665 3.599549 76.818068</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.410707</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_24</name>
		<expected>61.660207 -0.522258 -44.869326</expected>
		<detected>61.336749 -0.677733 -44.488921</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.727629</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_25</name>
		<expected>-67.110669 2.029161 69.932903</expected>
		<detected>-65.864191 2.522521 69.809059</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.668170</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_26</name>
		<expected>-60.133956 -1.980988 -51.801415</expected>
		<detected>-63.510325 -1.333324 -53.486084</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>3.063107</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_17</name>
		<expected>43.409529 -27.045122 64.897839</expected>
		<detected>42.860431 -27.129778 65.092274</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.191297</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_18</name>
		<expected>48.979462 -30.246668 -32.290051</expected>
		<detected>49.266335 -30.587091 -31.682765</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.566653</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_19</name>
		<expected>-53.826139 -28.209715 59.363531</expected>
		<detected>-53.430659 -28.354936 58.679897</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.868915</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_20</name>
		<expected>-48.256206 -31.411261 -37.824359</expected>
		<detected>-48.168992 -32.070916 -37.519081</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.969891</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_09</name>
		<expected>8.702725 -26.836683 81.542486</expected>
		<detected>8.636382 -26.855159 81.248764</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.752345</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_10</name>
		<expected>16.399983 -31.260996 -52.764393</expected>
		<detected>16.255961 -31.948082 -52.560606</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.449053</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_11</name>
		<expected>-21.246660 -27.195387 79.837873</expected>
		<detected>-20.002046 -27.262525 80.218425</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.180412</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_12</name>
		<expected>-13.549401 -31.619700 -54.469005</expected>
		<detected>-12.932645 -32.022047 -54.264669</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.059653</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_21</name>
		<expected>63.905322 -27.930447 32.328088</expected>
		<detected>64.109014 -28.286959 32.348974</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.535104</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_22</name>
		<expected>65.620907 -28.916549 2.393419</expected>
		<detected>66.377872 -29.066138 2.477808</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.348268</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_23</name>
		<expected>-70.467583 -29.539834 24.680061</expected>
		<detected>-70.644227 -29.968384 24.609922</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.389946</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_2_24</name>
		<expected>-68.751998 -30.525936 -5.254607</expected>
		<detected>-70.963875 -31.437272 -9.146056</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>3.916914</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_01</name>
		<expected>24.433946 -50.146007 44.126792</expected>
		<detected>24.020948 -50.967988 43.418272</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.224006</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_02</name>
		<expected>27.670683 -52.006453 -12.349949</expected>
		<detected>30.647650 -55.511542 -11.837322</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>4.104407</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_03</name>
		<expected>-32.070559 -50.822762 40.910757</expected>
		<detected>-31.989190 -51.043301 40.932588</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.337457</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_04</name>
		<expected>-28.833822 -52.683208 -15.565984</expected>
		<detected>-29.270311 -53.017605 -15.065797</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.780193</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_09</name>
		<expected>-37.917393 33.216366 96.034070</expected>
		<detected>-36.391371 33.688509 95.728687</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.602616</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_10</name>
		<expected>-28.035622 27.536416 -76.389620</expected>
		<detected>-27.236788 27.717786 -76.705836</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.365422</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_11</name>
		<expected>21.981376 33.933774 99.443294</expected>
		<detected>25.509015 31.294097 101.779656</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>4.478891</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_12</name>
		<expected>31.863146 28.253825 -72.980396</expected>
		<detected>30.397311 28.091889 -73.150151</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.438438</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_01</name>
		<expected>-87.565765 28.715924 -23.317114</expected>
		<detected>-88.715954 29.235231 -23.974778</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.640839</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_02</name>
		<expected>-90.996935 30.688129 36.552222</expected>
		<detected>-91.658009 31.359468 36.142573</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.639693</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_03</name>
		<expected>84.942689 30.782061 -13.498548</expected>
		<detected>85.483402 30.898463 -13.169623</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.186021</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_04</name>
		<expected>81.511519 32.754266 46.370788</expected>
		<detected>81.293521 33.028563 46.440764</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.157057</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_05</name>
		<expected>-3.571226 -56.389307 39.420252</expected>
		<detected>-3.311324 -56.608797 39.205469</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.414336</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_06</name>
		<expected>-0.711918 -58.032810 -10.470862</expected>
		<detected>-0.792512 -58.454352 -10.804913</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.267504</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_07</name>
		<expected>22.816248 -56.912138 15.895205</expected>
		<detected>23.281761 -57.168231 15.619584</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.498711</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_3_08</name>
		<expected>-27.099392 -57.509979 13.054185</expected>
		<detected>-27.357827 -58.160835 13.099323</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.240847</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_05</name>
		<expected>-71.317908 32.088184 72.409658</expected>
		<detected>-70.430686 33.049650 71.924481</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.565261</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_06</name>
		<expected>-63.918017 27.834795 -56.708545</expected>
		<detected>-63.112362 28.070826 -56.539097</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.719341</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_07</name>
		<expected>57.863771 33.635395 79.762219</expected>
		<detected>62.125201 30.940607 83.069169</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>5.268378</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_08</name>
		<expected>65.263661 29.382007 -49.355984</expected>
		<detected>64.223908 29.370206 -49.023878</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.397572</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_13</name>
		<expected>-8.259658 33.742707 102.827576</expected>
		<detected>-7.781119 34.608376 101.925793</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.417334</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_14</name>
		<expected>2.205411 27.727483 -79.773901</expected>
		<detected>1.756937 27.911833 -80.054426</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.294067</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_0_28</name>
		<expected>-94.372746 29.641047 6.327770</expected>
		<detected>-95.990784 29.735704 5.937234</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.840261</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_07</name>
		<expected>22.586355 3.777919 95.159788</expected>
		<detected>25.443058 1.458308 98.312171</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>4.247055</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_08</name>
		<expected>31.861952 -1.553607 -66.686986</expected>
		<detected>30.661919 -1.840815 -66.146085</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.368757</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_09</name>
		<expected>-37.312414 3.060511 91.750563</expected>
		<detected>-36.041912 3.328597 92.027593</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.313348</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_10</name>
		<expected>-28.036817 -2.271016 -70.096210</expected>
		<detected>-27.064159 -2.375004 -69.647980</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.703634</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_27</name>
		<expected>76.522353 2.709251 47.074592</expected>
		<detected>76.367691 2.875363 47.150490</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>1.079023</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_28</name>
		<expected>79.953524 0.737047 -12.794745</expected>
		<detected>80.561217 0.766647 -12.529327</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.253518</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_29</name>
		<expected>-85.403985 0.769857 37.858322</expected>
		<detected>-88.124749 1.398167 38.926812</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>2.648552</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_30</name>
		<expected>-81.972815 -1.202348 -22.011015</expected>
		<detected>-82.306407 -1.013155 -21.910711</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.806803</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_03</name>
		<expected>-7.671834 3.596714 98.843416</expected>
		<detected>-7.450877 3.651212 99.054341</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.188969</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_04</name>
		<expected>2.221373 -2.089810 -73.779839</expected>
		<detected>1.725092 -2.135897 -74.221054</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.354136</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_31</name>
		<expected>83.628828 1.787716 17.446754</expected>
		<detected>83.786232 1.587828 17.235572</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.828720</fitResidual>
	</landmark>
	<landmark>
		<name>10mm_1_32</name>
		<expected>-89.079289 -0.280812 7.616824</expected>
		<detected>-89.512003 -0.340826 7.573630</detected>
		<isPrecise>yes</isPrecise>
		<fitResidual>0.467125</fitResidual>
	</landmark>
</landmarkList>
</phantom>

