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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/rfove/ commit c045f067a57e8308308cf6329060c7ccd3fc372f
author imgteam
date Thu, 04 Apr 2024 15:26:16 +0000
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1 <tool id="rfove" name="Perform segmentation using region-based fitting of overlapping ellipses" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
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2 <description>with RFOVE</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@">2023.11.12</token>
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7 <token name="@VERSION_SUFFIX@">2</token>
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8 </macros>
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9 <creator>
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10 <expand macro="creators/bmcv"/>
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11 </creator>
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12 <edam_operations>
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13 <edam_operation>operation_3443</edam_operation>
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14 </edam_operations>
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15 <xrefs>
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16 <xref type="bio.tools">rfove</xref>
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17 </xrefs>
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18 <requirements>
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19 <container type="docker">docker.io/kostrykin/rfove:@TOOL_VERSION@</container>
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20 </requirements>
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21 <command detect_errors="aggressive">
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22 <![CDATA[
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23 #set $neighborhood_size = "%d" % ($half_neighborhood_size.value * 2 + 1)
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24 /rfove
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25 ${area_ub}
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26 ${min_area_max_area_ratio_ub}
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27 ${overlap_ub}
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28 ${neighborhood_size}
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29 '${dataset}'
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30
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31 output.tiff
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32 ]]>
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33 </command>
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34 <inputs>
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35 <param name="dataset" type="data" format="tiff,png" label="Input image" />
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36 <param name="area_ub" type="integer" label="Maximum ellipse area" min="5" value="250" />
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37 <param name="min_area_max_area_ratio_ub" type="float" min="0" max="1" value="0.1" label="Upper bound of the ratio: minimum area / maximum area" />
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38
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39 <param name="overlap_ub" type="float" label="Maximum ellipse overlap" min="0" value="0.2" />
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40 <param name="half_neighborhood_size" type="integer" label="Half neighborhood size" min="1" value="100" />
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41 </inputs>
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42 <outputs>
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43 <data format="tiff" name="masks" from_work_dir="output.tiff" label="${tool.name} on ${on_string}" />
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44 </outputs>
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45 <tests>
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46 <test>
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47 <param name="dataset" value="BBBC033_C2_z28.png" />
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48 <expand macro="tests/label_image_diff" name="masks" value="output.tiff" ftype="tiff"/>
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49 </test>
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50 </tests>
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51 <help>
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52
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53 **Perform segmentation using shape decomposition based on elliptical models and expectation maximization.**
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54
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55 RFOVE is completely unsupervised, operates without any assumption or prior knowledge on the object's shape
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56 and extends and improves the *Decremental Ellipse Fitting Algorithm* (DEFA). Both RFOVE and DEFA solve the
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57 multi-ellipse fitting problem by performing model selection that is guided by the minimization of the
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58 *Akaike Information Criterion* on a suitably defined shape complexity measure. However, in contrast to
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59 DEFA, RFOVE minimizes an objective function that allows for ellipses with higher degree of overlap and,
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60 thus, achieves better ellipse-based shape approximation.
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61
0
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62 </help>
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63 <citations>
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64 <citation type="doi">10.1016/j.imavis.2019.09.001</citation>
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65 </citations>
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66 </tool>