annotate skimage.xml @ 2:c84400b58260 draft default tip

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit c20c8e46a6391ec9759f1ae513ce0a779933af96
author imgteam
date Tue, 06 Jan 2026 01:38:25 +0000
parents b8867c9e0526
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1 <tool id="ridge_filter_skimage" name="Apply ridge filter" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
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2 <description>with scikit-image</description>
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3 <macros>
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4 <import>creators.xml</import>
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5 <import>tests.xml</import>
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6 <token name="@TOOL_VERSION@">0.22.0</token>
2
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7 <token name="@VERSION_SUFFIX@">2</token>
0
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8 <xml name="base_params">
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9 <param name="black_ridges" type="select" label="Mode of operation">
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10 <option value="true" selected="true">Enhance dark ridges (low image intensities)</option>
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11 <option value="false">Enhance bright ridges (high image intensities)</option>
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12 </param>
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13 <param name="sigma_min" type="float" value="1" min="0.1" label="Minimum sigma" help="Lower bound of the scale for multi-scale analysis."/>
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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14 <param name="sigma_max" type="float" value="3" min="0.1" label="Maximum sigma" help="Upper bound of the scale for multi-scale analysis."/>
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15 <param name="num_sigma" type="integer" value="10" min="2" label="Number of sigma steps for multi-scale analysis"/>
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16 </xml>
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17 <xml name="frangi_params">
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18 <expand macro="base_params"/>
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19 <param name="alpha" type="float" min="0" value="0.5" label="Alpha"
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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20 help="Frangi correction constant that adjusts the filter's sensitivity to deviation from a plate-like structure."/>
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21 <param name="beta" type="float" min="0" value="0.5" label="Beta"
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22 help="Frangi correction constant that adjusts the filter's sensitivity to deviation from a blob-like structure."/>
2
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23 <param name="gamma" type="float" min="0" value="" label="Gamma" optional="true"
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24 help="Frangi correction constant that adjusts the filter's sensitivity to areas of high variance/texture/structure. Leave empty to use the default."/>
0
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25 </xml>
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26 </macros>
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27 <creator>
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28 <expand macro="creators/bmcv"/>
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29 <expand macro="creators/kostrykin"/>
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30 </creator>
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31 <edam_operations>
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32 <edam_operation>operation_3443</edam_operation>
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33 </edam_operations>
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34 <xrefs>
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35 <xref type="bio.tools">galaxy_image_analysis</xref>
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36 <xref type="bio.tools">scikit-image</xref>
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37 <xref type="biii">scikit-image</xref>
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38 </xrefs>
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39 <requirements>
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40 <requirement type="package" version="@TOOL_VERSION@">scikit-image</requirement>
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41 <requirement type="package" version="0.5.2">giatools</requirement>
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42 </requirements>
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43 <command detect_errors="aggressive"><![CDATA[
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44
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45 python '$__tool_directory__/filter_skimage.py'
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46
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47 '$input'
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48 '$output'
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49 '$params'
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50
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51 ]]></command>
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52 <configfiles>
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53 <configfile name="params"><![CDATA[
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54 {
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55
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56 #if $filter.filter_type == "frangi" or $filter.filter_type == "hessian" or $filter.filter_type == "meijering" or $filter.filter_type == "sato"
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57 "black_ridges": $filter.black_ridges,
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58 "sigma_min": $filter.sigma_min,
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59 "sigma_max": $filter.sigma_max,
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60 "num_sigma": $filter.num_sigma,
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61 #end if
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62
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63 #if $filter.filter_type == "frangi" or $filter.filter_type == "hessian"
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64 "alpha": $filter.alpha,
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65 "beta": $filter.beta,
2
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66 #if str($filter.gamma) != ""
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67 "gamma": $filter.gamma,
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68 #end if
0
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69 #end if
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70
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71 #if $filter.filter_type == "laplace"
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72 "ksize": $filter.ksize,
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73 #end if
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74
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75 "dtype": "$dtype",
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76 "filter_type": "$filter.filter_type"
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77
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78 }
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79 ]]></configfile>
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80 </configfiles>
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81 <inputs>
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82 <param name="input" type="data" format="tiff,png" label="Input image"/>
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83 <param name="dtype" type="select" label="Output pixel type"
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84 help="Data type used to store the pixel values in the output image.">
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85 <option value="float64" selected="True">64-bit floating point</option>
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86 <option value="float32">32-bit floating point</option>
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87 <option value="float16">16-bit floating point</option>
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88 </param>
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89 <conditional name="filter">
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90 <param name="filter_type" type="select" label="Filter">
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91 <option value="frangi" selected="True">Frangi vesselness filter</option>
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92 <option value="hessian">Hybrid Hessian filter</option>
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93 <option value="laplace">Laplace filter</option>
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94 <option value="meijering">Meijering neuriteness filter</option>
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95 <option value="sato">Sato tubeness filter</option>
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96 </param>
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97 <when value="frangi">
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98 <expand macro="frangi_params"/>
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99 </when>
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100 <when value="hessian">
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101 <expand macro="frangi_params"/>
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102 </when>
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103 <when value="laplace">
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104 <param name="ksize" type="integer" value="3" label="Kernel size"
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105 help="Define the size of the discrete Laplacian operator such that it will have the size of a hypercube with this edge length (in pixels)."/>
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106 </when>
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107 <when value="meijering">
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108 <expand macro="base_params"/>
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109 </when>
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110 <when value="sato">
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111 <expand macro="base_params"/>
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112 </when>
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113 </conditional>
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114 </inputs>
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115 <outputs>
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116 <data format="tiff" name="output"/>
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117 </outputs>
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118 <tests>
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119 <!-- Single-image (Q), Single-frame (T), Single-slice (Z), multi-channel (C), Frangi (dark) -->
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120 <test>
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121 <param name="input" value="scikit-image/retina.png"/>
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122 <param name="dtype" value="float16"/>
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123 <conditional name="filter">
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124 <param name="filter_type" value="frangi"/>
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125 <param name="black_ridges" value="true"/>
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126 <param name="sigma_min" value="0.5"/>
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127 <param name="sigma_max" value="20"/>
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128 <param name="num_sigma" value="10"/>
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129 <param name="alpha" value="0.5"/>
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130 <param name="beta" value="0.5"/>
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131 </conditional>
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132 <expand macro="tests/intensity_image_diff" name="output" value="retina_frangi.tiff" ftype="tiff"/>
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133 <assert_stdout>
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134 <has_line line='Applying filter: "frangi"'/>
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135 <has_line line="Performing 2-D filtering"/>
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136 </assert_stdout>
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137 </test>
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138 <!-- Single-image (Q), Single-frame (T), Single-slice (Z), single-channel (C), Hessian (dark) -->
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139 <test>
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140 <param name="input" value="retina_0c_0z_0t_0q.tiff"/>
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141 <param name="dtype" value="float16"/>
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142 <conditional name="filter">
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143 <param name="filter_type" value="hessian"/>
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144 <param name="black_ridges" value="true"/>
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145 <param name="sigma_min" value="0.5"/>
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146 <param name="sigma_max" value="20"/>
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147 <param name="num_sigma" value="10"/>
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148 <param name="alpha" value="0.5"/>
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149 <param name="beta" value="0.5"/>
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150 </conditional>
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151 <expand macro="tests/intensity_image_diff" name="output" value="retina_0c_0z_0t_0q_hessian.tiff" ftype="tiff"/>
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152 <assert_stdout>
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153 <has_line line='Applying filter: "hessian"'/>
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154 <has_line line="Performing 2-D filtering"/>
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155 </assert_stdout>
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156 </test>
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157 <!-- Single-image (Q), Multi-frame (T), Single-slice (Z), single-channel (C), Meijering (dark) -->
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158 <test>
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159 <param name="input" value="retina_0c_0z_3t_0q.tiff"/>
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160 <param name="dtype" value="float16"/>
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161 <conditional name="filter">
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162 <param name="filter_type" value="meijering"/>
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163 <param name="black_ridges" value="true"/>
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164 <param name="sigma_min" value="0.5"/>
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165 <param name="sigma_max" value="20"/>
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166 <param name="num_sigma" value="10"/>
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167 </conditional>
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168 <expand macro="tests/intensity_image_diff" name="output" value="retina_0c_0z_3t_0q_meijering.tiff" ftype="tiff"/>
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169 <assert_stdout>
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170 <has_line line='Applying filter: "meijering"'/>
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171 <has_line line="Performing 2-D filtering"/>
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172 </assert_stdout>
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173 </test>
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174 <!-- Multi-image (Q), Single-frame (T), Single-slice (Z), single-channel (C), Sato (dark) -->
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175 <test>
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176 <param name="input" value="retina_0c_0z_0t_2q.tiff"/>
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177 <param name="dtype" value="float16"/>
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178 <conditional name="filter">
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179 <param name="filter_type" value="sato"/>
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180 <param name="black_ridges" value="true"/>
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181 <param name="sigma_min" value="0.5"/>
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182 <param name="sigma_max" value="20"/>
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183 <param name="num_sigma" value="10"/>
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184 </conditional>
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185 <expand macro="tests/intensity_image_diff" name="output" value="retina_0c_0z_0t_2q_sato.tiff" ftype="tiff"/>
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186 <assert_stdout>
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187 <has_line line='Applying filter: "sato"'/>
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188 <has_line line="Performing 2-D filtering"/>
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189 </assert_stdout>
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190 </test>
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191 <!-- Single-image (Q), Single-frame (T), Multi-slice (Z), single-channel (C), Laplace -->
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192 <test>
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193 <param name="input" value="retina_0c_5z_0t_0q.tiff"/>
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194 <param name="dtype" value="float16"/>
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195 <conditional name="filter">
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196 <param name="filter_type" value="laplace"/>
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197 <param name="ksize" value="5"/>
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198 </conditional>
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199 <expand macro="tests/intensity_image_diff" name="output" value="retina_0c_5z_0t_0q_laplace.tiff" ftype="tiff"/>
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200 <assert_stdout>
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201 <has_line line='Applying filter: "laplace"'/>
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202 <has_line line="Performing 3-D filtering"/>
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203 </assert_stdout>
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204 </test>
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205 <!-- Bright ridges, Single-image (Q), Single-frame (T), Multi-slice (Z), single-channel (C), Frangi (bright) -->
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206 <test>
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207 <param name="input" value="retina_inv_0c_0z_0t_0q.tiff"/>
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208 <param name="dtype" value="float16"/>
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209 <conditional name="filter">
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210 <param name="filter_type" value="frangi"/>
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211 <param name="black_ridges" value="false"/>
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212 <param name="sigma_min" value="0.5"/>
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213 <param name="sigma_max" value="20"/>
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214 <param name="num_sigma" value="10"/>
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215 <param name="alpha" value="0.5"/>
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216 <param name="beta" value="0.5"/>
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217 </conditional>
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218 <expand macro="tests/intensity_image_diff" name="output" value="retina_inv_0c_0z_0t_0q_frangi.tiff" ftype="tiff"/>
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219 <assert_stdout>
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220 <has_line line='Applying filter: "frangi"'/>
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221 <has_line line="Performing 2-D filtering"/>
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222 </assert_stdout>
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223 </test>
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224 </tests>
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225 <help>
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226
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227 **Applies a ridge filter to an image.**
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228
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229 Ridge filters can be used to detect ridge-like structures, such as neurites, tubes, vessels, wrinkles, or rivers. Different
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230 ridge filters may be suited for detecting different structures, e.g., depending on contrast or noise level. 2-D and 3-D
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231 images are supported. For multi-channel images, the filter is applied to all channels of the image. For time-series images,
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232 the filter is also applied for all time steps.
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233
1
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234 .. class:: warningmark
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235
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236 **Attention:** For proper results, this tool requires the image data to be scaled isotropically (pixels/voxels must be
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237 isotropic). Consider re-scaling the data with the `Scale image`_ tool, if necessary.
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238
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239 .. _Scale image: ?tool_id=toolshed.g2.bx.psu.edu/repos/imgteam/scale_image/ip_scale_image
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240
0
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241 Frangi vesselness filter
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242 ========================
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243
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244 Filter an image with the Frangi vesselness filter. This filter can be used to detect continuous ridges, e.g. vessels,
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245 wrinkles, rivers. It can be used to calculate the fraction of the whole image containing such objects. Calculates the
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246 eigenvalues of the Hessian to compute the similarity of an image region to vessels, according to the method described in
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247 Frangi et al. (1998).
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248
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249 Hybrid Hessian filter
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250 =====================
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251
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252 Filter an image with the Hybrid Hessian filter (Schrijver 2001, Kroon 2009). This filter can be used to detect continuous
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253 edges, e.g. vessels, wrinkles, rivers. It can be used to calculate the fraction of the whole image containing such objects.
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254 Almost equal to Frangi filter, but uses alternative method of smoothing.
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255
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256 Laplace filter
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257 ==============
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258
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259 Find the edges of an image using the Laplace operator.
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260
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261 Meijering neuriteness filter
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262 ============================
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263
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264 Filter an image with the Meijering neuriteness filter. This filter can be used to detect continuous ridges, e.g. neurites,
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265 wrinkles, rivers. It can be used to calculate the fraction of the whole image containing such objects. Calculates the
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266 eigenvalues of the Hessian to compute the similarity of an image region to neurites, according to the method described in
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267 Meijering et al. (2004).
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268
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269 Sato tubeness filter
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270 ====================
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271
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272 Filter an image with the Sato tubeness filter. This filter can be used to detect continuous ridges, e.g. tubes, wrinkles,
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273 rivers. It can be used to calculate the fraction of the whole image containing such objects. Calculates the eigenvalues of
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274 the Hessian to compute the similarity of an image region to tubes, according to the method described in Sato et al. (1998).
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275
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276 </help>
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277 <citations>
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278 <citation type="doi">10.1007/BFb0056195</citation>
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279 <citation type="doi">10.1002/cyto.a.20022</citation>
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280 <citation type="doi">10.1016/S1361-8415(98)80009-1</citation>
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281 </citations>
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282 </tool>