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feat(info): change some info as per publish requirements
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linhandev committed Sep 5, 2022
1 parent 45f315c commit 173ce5e
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11 changes: 6 additions & 5 deletions CMakeLists.txt
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@@ -1,15 +1,16 @@
cmake_minimum_required(VERSION 3.16.3...3.19.7 FATAL_ERROR)

project(EISeg)
project(EIMedSeg3D)

#-----------------------------------------------------------------------------
# Extension meta-information
set(EXTENSION_HOMEPAGE "https://www.slicer.org/wiki/Documentation/Nightly/Extensions/EISeg")
set(EXTENSION_HOMEPAGE "https://github.com/PaddleCV-SIG/SlicerEIMedSeg3D")
set(EXTENSION_CATEGORY "Segmentation")
set(EXTENSION_CONTRIBUTORS "Shiyu Tang (Baidu Co.), Lin Han (NYU Tandon School of Engineering)")
set(EXTENSION_DESCRIPTION "EISeg")
set(EXTENSION_ICONURL "https://www.example.com/Slicer/Extensions/EISeg.png")
set(EXTENSION_SCREENSHOTURLS "https://www.example.com/Slicer/Extensions/EISeg/Screenshots/1.png")
set(EXTENSION_DESCRIPTION "A 3D slicer extension for performing Efficient Interactive Medical image Segmentation in 3D. Users guide a deep learning model to perform segmentation by providing positive and negative points.
")
set(EXTENSION_ICONURL "https://github.com/PaddleCV-SIG/SlicerEIMedSeg3D/releases/download/v0.1.0/EIMedSeg3D.png")
set(EXTENSION_SCREENSHOTURLS "https://github.com/PaddleCV-SIG/SlicerEIMedSeg3D/releases/download/v0.1.0/screenshot.png")
set(EXTENSION_DEPENDS "NA") # Specified as a list or "NA" if no dependencies

#-----------------------------------------------------------------------------
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6 changes: 3 additions & 3 deletions EIMedSeg3D/CMakeLists.txt
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@@ -1,5 +1,5 @@
#-----------------------------------------------------------------------------
set(MODULE_NAME placePoint)
set(MODULE_NAME EIMedSeg3D)

#-----------------------------------------------------------------------------
set(MODULE_PYTHON_SCRIPTS
Expand All @@ -24,8 +24,8 @@ if(BUILD_TESTING)

# Register the unittest subclass in the main script as a ctest.
# Note that the test will also be available at runtime.
slicer_add_python_unittest(SCRIPT ${MODULE_NAME}.py)
# slicer_add_python_unittest(SCRIPT ${MODULE_NAME}.py)

# Additional build-time testing
add_subdirectory(Testing)
# add_subdirectory(Testing)
endif()
9 changes: 3 additions & 6 deletions EIMedSeg3D/EIMedSeg3D.py
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Expand Up @@ -74,19 +74,16 @@ def __init__(self, parent):
ScriptedLoadableModule.__init__(self, parent)
self.parent.title = "EIMedSeg3D" # TODO: make this more human readable by adding spaces
self.parent.categories = [
"Interactive Segmentation"
"Segmentation"
] # TODO: set categories (folders where the module shows up in the module selector)
self.parent.dependencies = [] # TODO: add here list of module names that this module requires
self.parent.contributors = ["Lin Han, Daisy (Baidu Corp.)"]
self.parent.contributors = ["Lin Han(NYU Tandon School of Engineering), Daisy (Baidu Corp.)"]
# TODO: update with short description of the module and a link to online module documentation
self.parent.helpText = """
This is an example of scripted loadable module bundled in an extension.
See more information in <a href="https://github.com/organization/projectname#EIMedSeg3D">module documentation</a>.
An extension to perform efficient interactive segmentation with help from deep learning. Specify model and parameter paths, load model, select a data folder and add positive or negative points to get segmentation result.
"""
# TODO: replace with organization, grant and thanks
self.parent.acknowledgementText = """
This file was originally developed by Jean-Christophe Fillion-Robin, Kitware Inc., Andras Lasso, PerkLab,
and Steve Pieper, Isomics, Inc. and was partially funded by NIH grant 3P41RR013218-12S1.
"""

# Additional initialization step after application startup is complete
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6 changes: 0 additions & 6 deletions EIMedSeg3D/test_MR/labels.txt

This file was deleted.

4 changes: 2 additions & 2 deletions README.md
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@@ -1,6 +1,6 @@
# SlicerEISeg
# SlicerEIMedSeg3D

3D slicer extension for interactive medical image segmentation
A 3D slicer extension for performing **E**fficient **I**nteractive **Med**ical image **Seg**mentation in **3D**. Users guide a deep learning model to perform segmentation by providing positive and negative points.

## Install

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