diff --git a/.github/workflows/auto-test-dependencies_timed.yml b/.github/workflows/auto-test-dependencies_timed.yml
index 61acd87b..6fc6640a 100644
--- a/.github/workflows/auto-test-dependencies_timed.yml
+++ b/.github/workflows/auto-test-dependencies_timed.yml
@@ -3,7 +3,7 @@
# Automated tests are run at 6:30 UTC on the first and fifteenth day of each month.
-name: Run automated tests on multiple platforms to detect dependency issues
+name: build-check
on:
workflow_dispatch:
diff --git a/NEWS.md b/NEWS.md
index 27074d61..a99a6a76 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,9 @@
+# Version 2.2.4
+
+## Fixes
+
+- Masks can now be plotted in images without causing an error when using `matplotlib` version 3.9.0 or later.
+
# Version 2.2.3
## Minor changes
@@ -7,7 +13,7 @@
- MIRP now checks whether there are potential problems between the frames of reference of image and mask files.
-# Fixes
+## Fixes
- Fixed an error that occurs when attempting to create a deep copy `ImageITKFile` objects.
diff --git a/README.md b/README.md
index d0d90904..449f2015 100644
--- a/README.md
+++ b/README.md
@@ -1,14 +1,35 @@
+![GitHub License](https://img.shields.io/github/license/oncoray/mirp)
+![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mirp)
+[![PyPI - Version](https://img.shields.io/pypi/v/mirp)](https://pypi.org/project/mirp/)
+![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/oncoray/mirp/auto-test-dependencies_timed.yml)
+[![JOSS](https://joss.theoj.org/papers/165c85b1ecad891550a21b12c8b2e577/status.svg)](https://joss.theoj.org/papers/165c85b1ecad891550a21b12c8b2e577)
+
# Medical Image Radiomics Processor
-Medical Image Radiomics Processor (MIRP) is a python package for medical image analysis that is compliant with the
-reference standards of the Image Biomarker Standardisation Initiative (IBSI). MIRP focuses on radiomics applications
-and supports computation of features for conventional radiomics and image processing for deep-learning applications.
+MIRP is a python package for quantitative analysis of medical images. It focuses on processing images for integration
+with radiomics workflows. These workflows either use quantitative features computed using MIRP, or directly use MIRP
+to process images as input for neural networks and other deep learning models.
+
+MIRP offers the following main functionality:
+
+- [Extract and collect metadata](https://oncoray.github.io/mirp/image_metadata.html) from medical images.
+- [Find and collect labels or names](https://oncoray.github.io/mirp/mask_labels.html) of regions of interest from image
+ segmentations.
+- [Compute quantitative features](https://oncoray.github.io/mirp/quantitative_image_analysis.html) from regions of interest in medical images.
+- [Process images for deep learning](https://oncoray.github.io/mirp/deep_learning.html).
+
+## Tutorials
+
+We currently offer the following tutorials:
+
+- [Computing quantitative features from MR images](https://oncoray.github.io/mirp/tutorial_compute_radiomics_features_mr.html)
+- [Applying filters to images](https://oncoray.github.io/mirp/tutorial_apply_image_filter.html)
-## Documentation and tutorials
+## Documentation
-Documentation and tutorials can be found here: https://oncoray.github.io/mirp/
+Documentation can be found here: https://oncoray.github.io/mirp/
## Supported Python and OS
diff --git a/docs/.buildinfo b/docs/.buildinfo
index 92258720..72a9ef27 100644
--- a/docs/.buildinfo
+++ b/docs/.buildinfo
@@ -1,4 +1,4 @@
# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: b7d3c05f6bec86800f0a1510ac564b73
+config: 92a05a2b300f0adee19d846b9e8f30a1
tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/docs/_images/tutorial_apply_image_filter_13_0.png b/docs/_images/tutorial_apply_image_filter_14_0.png
similarity index 100%
rename from docs/_images/tutorial_apply_image_filter_13_0.png
rename to docs/_images/tutorial_apply_image_filter_14_0.png
diff --git a/docs/_images/tutorial_apply_image_filter_15_0.png b/docs/_images/tutorial_apply_image_filter_16_0.png
similarity index 100%
rename from docs/_images/tutorial_apply_image_filter_15_0.png
rename to docs/_images/tutorial_apply_image_filter_16_0.png
diff --git a/docs/_images/tutorial_apply_image_filter_17_0.png b/docs/_images/tutorial_apply_image_filter_18_0.png
similarity index 100%
rename from docs/_images/tutorial_apply_image_filter_17_0.png
rename to docs/_images/tutorial_apply_image_filter_18_0.png
diff --git a/docs/_images/tutorial_apply_image_filter_19_0.png b/docs/_images/tutorial_apply_image_filter_20_0.png
similarity index 100%
rename from docs/_images/tutorial_apply_image_filter_19_0.png
rename to docs/_images/tutorial_apply_image_filter_20_0.png
diff --git a/docs/_images/tutorial_apply_image_filter_21_0.png b/docs/_images/tutorial_apply_image_filter_22_0.png
similarity index 100%
rename from docs/_images/tutorial_apply_image_filter_21_0.png
rename to docs/_images/tutorial_apply_image_filter_22_0.png
diff --git a/docs/_images/tutorial_apply_image_filter_23_0.png b/docs/_images/tutorial_apply_image_filter_24_0.png
similarity index 100%
rename from docs/_images/tutorial_apply_image_filter_23_0.png
rename to docs/_images/tutorial_apply_image_filter_24_0.png
diff --git a/docs/_images/tutorial_apply_image_filter_25_0.png b/docs/_images/tutorial_apply_image_filter_26_0.png
similarity index 100%
rename from docs/_images/tutorial_apply_image_filter_25_0.png
rename to docs/_images/tutorial_apply_image_filter_26_0.png
diff --git a/docs/_images/tutorial_apply_image_filter_7_0.png b/docs/_images/tutorial_apply_image_filter_8_0.png
similarity index 100%
rename from docs/_images/tutorial_apply_image_filter_7_0.png
rename to docs/_images/tutorial_apply_image_filter_8_0.png
diff --git a/docs/_images/tutorial_compute_radiomics_features_mr_7_0.png b/docs/_images/tutorial_compute_radiomics_features_mr_7_0.png
deleted file mode 100644
index ac067068..00000000
Binary files a/docs/_images/tutorial_compute_radiomics_features_mr_7_0.png and /dev/null differ
diff --git a/docs/_images/tutorial_compute_radiomics_features_mr_8_0.png b/docs/_images/tutorial_compute_radiomics_features_mr_8_0.png
new file mode 100644
index 00000000..210c438e
Binary files /dev/null and b/docs/_images/tutorial_compute_radiomics_features_mr_8_0.png differ
diff --git a/docs/_modules/index.html b/docs/_modules/index.html
index 173b7822..f32ad8f9 100644
--- a/docs/_modules/index.html
+++ b/docs/_modules/index.html
@@ -3,8 +3,8 @@
- Overview: module code — mirp 2.2.3 documentation
-
+ Overview: module code — mirp 2.2.4 documentation
+
@@ -14,7 +14,7 @@
-
+
@@ -52,7 +52,7 @@
Tutorial: Computing radiomics features
Tutorial: Applying image filters
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
Configure image and mask import
Configure the image processing and feature extraction workflow
diff --git a/docs/_sources/index.rst.txt b/docs/_sources/index.rst.txt
index 90e5b0d2..d35e3470 100644
--- a/docs/_sources/index.rst.txt
+++ b/docs/_sources/index.rst.txt
@@ -20,7 +20,7 @@ MIRP
.. toctree::
:hidden:
:maxdepth: 1
- :caption: Deep Dive
+ :caption: Documentation and API
image_mask_import
configuration
diff --git a/docs/_sources/tutorial_apply_image_filter.ipynb.txt b/docs/_sources/tutorial_apply_image_filter.ipynb.txt
index 55e2b357..8b19f93c 100644
--- a/docs/_sources/tutorial_apply_image_filter.ipynb.txt
+++ b/docs/_sources/tutorial_apply_image_filter.ipynb.txt
@@ -1,5 +1,20 @@
{
"cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "67197b42-8edc-4eee-aafc-c2b48d3aee4f",
+ "metadata": {
+ "nbsphinx": "hidden"
+ },
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "import warnings\n",
+ "sys.path.append(r\"C:\\Users\\alexz\\Documents\\GitHub\\mirp\")\n",
+ "warnings.filterwarnings('ignore')"
+ ]
+ },
{
"cell_type": "markdown",
"id": "1e447b05-08e1-4326-9709-531acf639a69",
@@ -163,7 +178,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "INFO\t: MainProcess \t 2024-06-05 11:52:36,662 \t Initialising image extraction using ct images for 1.\n"
+ "INFO\t: MainProcess \t 2024-06-18 08:26:19,447 \t Initialising image extraction using ct images for 1.\n"
]
}
],
@@ -348,7 +363,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "INFO\t: MainProcess \t 2024-06-05 11:52:38,720 \t Initialising image extraction using ct images for 1.\n"
+ "INFO\t: MainProcess \t 2024-06-18 08:26:22,640 \t Initialising image extraction using ct images for 1.\n"
]
}
],
@@ -603,7 +618,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "INFO\t: MainProcess \t 2024-06-05 11:52:54,562 \t Initialising feature computation using ct images for 1.\n"
+ "INFO\t: MainProcess \t 2024-06-18 08:26:38,268 \t Initialising feature computation using ct images for 1.\n"
]
},
{
diff --git a/docs/_sources/tutorial_compute_radiomics_features_mr.ipynb.txt b/docs/_sources/tutorial_compute_radiomics_features_mr.ipynb.txt
index 24af350a..9eac0566 100644
--- a/docs/_sources/tutorial_compute_radiomics_features_mr.ipynb.txt
+++ b/docs/_sources/tutorial_compute_radiomics_features_mr.ipynb.txt
@@ -1,5 +1,20 @@
{
"cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "2830a672-16e3-4b55-a9b5-d404399e7991",
+ "metadata": {
+ "nbsphinx": "hidden"
+ },
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "import warnings\n",
+ "sys.path.append(r\"C:\\Users\\alexz\\Documents\\GitHub\\mirp\")\n",
+ "warnings.filterwarnings('ignore')"
+ ]
+ },
{
"cell_type": "markdown",
"id": "1e447b05-08e1-4326-9709-531acf639a69",
@@ -268,7 +283,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "INFO\t: MainProcess \t 2024-06-05 11:55:22,262 \t Initialising image extraction using mr images for STS_003.\n"
+ "INFO\t: MainProcess \t 2024-06-20 17:08:52,671 \t Initialising image extraction using mr images for STS_003.\n"
]
}
],
@@ -299,7 +314,7 @@
"outputs": [
{
"data": {
- "image/png": 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",
+ "image/png": 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@@ -529,9 +544,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "INFO\t: MainProcess \t 2024-06-05 11:55:23,768 \t Initialising feature computation using mr images for STS_001.\n",
- "INFO\t: MainProcess \t 2024-06-05 11:55:36,474 \t Initialising feature computation using mr images for STS_002.\n",
- "INFO\t: MainProcess \t 2024-06-05 11:55:46,159 \t Initialising feature computation using mr images for STS_003.\n"
+ "INFO\t: MainProcess \t 2024-06-20 17:08:54,208 \t Initialising feature computation using mr images for STS_001.\n",
+ "INFO\t: MainProcess \t 2024-06-20 17:09:07,088 \t Initialising feature computation using mr images for STS_002.\n",
+ "INFO\t: MainProcess \t 2024-06-20 17:09:16,781 \t Initialising feature computation using mr images for STS_003.\n"
]
},
{
diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js
index e21a8f99..91a92f56 100644
--- a/docs/_static/documentation_options.js
+++ b/docs/_static/documentation_options.js
@@ -1,5 +1,5 @@
const DOCUMENTATION_OPTIONS = {
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+ VERSION: '2.2.4',
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BUILDER: 'html',
diff --git a/docs/_static/pygments.css b/docs/_static/pygments.css
index 84ab3030..08bec689 100644
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index 75eae56c..7e6dae14 100644
--- a/docs/configuration.html
+++ b/docs/configuration.html
@@ -1,11 +1,11 @@
-
+
- Configure the image processing and feature extraction workflow — mirp 2.2.3 documentation
-
+ Configure the image processing and feature extraction workflow — mirp 2.2.4 documentation
+
@@ -15,7 +15,7 @@
-
+
@@ -55,7 +55,7 @@
Tutorial: Computing radiomics features
Tutorial: Applying image filters
-Deep Dive
+Documentation and API
Configure image and mask import
Configure the image processing and feature extraction workflow
diff --git a/docs/contributing.html b/docs/contributing.html
index 79714a64..0ffc580e 100644
--- a/docs/contributing.html
+++ b/docs/contributing.html
@@ -1,11 +1,11 @@
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+
- Contributing — mirp 2.2.3 documentation
-
+ Contributing — mirp 2.2.4 documentation
+
@@ -15,7 +15,7 @@
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+
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Tutorial: Computing radiomics features
Tutorial: Applying image filters
-Deep Dive
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+Documentation and API
-Deep Dive
+Documentation and API
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+Documentation and API
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+Documentation and API
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-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
Configure image and mask import
Configure the image processing and feature extraction workflow
@@ -117,9 +117,9 @@ What can MIRP help you do?
-
-
-
+
+
+
File format
@@ -156,10 +156,10 @@ Supported image and mask modalities
-
-
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+
+
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Python
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index 149a0b41..806034fb 100644
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+
- Installing MIRP — mirp 2.2.3 documentation
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+ Installing MIRP — mirp 2.2.4 documentation
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+
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Tutorial: Computing radiomics features
Tutorial: Applying image filters
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+Documentation and API
-Deep Dive
+Documentation and API
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+Documentation and API
-Deep Dive
+Documentation and API
-Deep Dive
+Documentation and API
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+Documentation and API
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Configure the image processing and feature extraction workflow
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index 7c251081..04cb1879 100644
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\ No newline at end of file
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image filter example": [[12, "basic-image-filter-example"]], "Image filter with additional features": [[12, "image-filter-with-additional-features"]], "Tutorial: Applying image filters": [[13, "Tutorial:-Applying-image-filters"]], "Download example data": [[13, "Download-example-data"], [14, "Download-example-data"]], "Finding mask labels": [[13, "Finding-mask-labels"], [14, "Finding-mask-labels"]], "Visualising images": [[13, "Visualising-images"], [14, "Visualising-images"]], "Assessing image metadata": [[13, "Assessing-image-metadata"], [14, "Assessing-image-metadata"]], "Applying filters": [[13, "Applying-filters"]], "Mean filter": [[13, "Mean-filter"]], "Laplacian-of-Gaussian filter": [[13, "Laplacian-of-Gaussian-filter"]], "Nonseparable Simoncelli wavelet filter": [[13, "Nonseparable-Simoncelli-wavelet-filter"]], "Computing features": [[13, "Computing-features"], [14, "Computing-features"]], "Tutorial: Computing radiomics features": [[14, "Tutorial:-Computing-radiomics-features"]]}, "indexentries": {"featureextractionsettingsclass (class in mirp.settings.feature_parameters)": [[0, "mirp.settings.feature_parameters.FeatureExtractionSettingsClass"]], "generalsettingsclass (class in mirp.settings.general_parameters)": [[0, "mirp.settings.general_parameters.GeneralSettingsClass"]], "imageinterpolationsettingsclass (class in mirp.settings.interpolation_parameters)": [[0, "mirp.settings.interpolation_parameters.ImageInterpolationSettingsClass"]], "imageperturbationsettingsclass (class in mirp.settings.perturbation_parameters)": [[0, "mirp.settings.perturbation_parameters.ImagePerturbationSettingsClass"]], "imagepostprocessingclass (class in mirp.settings.image_processing_parameters)": [[0, "mirp.settings.image_processing_parameters.ImagePostProcessingClass"]], "imagetransformationsettingsclass (class in mirp.settings.transformation_parameters)": [[0, "mirp.settings.transformation_parameters.ImageTransformationSettingsClass"]], "maskinterpolationsettingsclass (class in mirp.settings.interpolation_parameters)": [[0, "mirp.settings.interpolation_parameters.MaskInterpolationSettingsClass"]], "resegmentationsettingsclass (class in mirp.settings.resegmentation_parameters)": [[0, "mirp.settings.resegmentation_parameters.ResegmentationSettingsClass"]], "settingsclass (class in mirp.settings.generic)": [[0, "mirp.settings.generic.SettingsClass"]], "get_settings_xml() (in module mirp.utilities.config_utilities)": [[0, "mirp.utilities.config_utilities.get_settings_xml"]], "mirp.settings.feature_parameters": [[0, "module-mirp.settings.feature_parameters"]], "mirp.settings.general_parameters": [[0, "module-mirp.settings.general_parameters"]], "mirp.settings.generic": [[0, "module-mirp.settings.generic"]], "mirp.settings.image_processing_parameters": [[0, "module-mirp.settings.image_processing_parameters"]], "mirp.settings.interpolation_parameters": [[0, "module-mirp.settings.interpolation_parameters"]], "mirp.settings.perturbation_parameters": [[0, "module-mirp.settings.perturbation_parameters"]], "mirp.settings.resegmentation_parameters": [[0, "module-mirp.settings.resegmentation_parameters"]], "mirp.settings.transformation_parameters": [[0, "module-mirp.settings.transformation_parameters"]], "module": [[0, "module-mirp.settings.feature_parameters"], [0, "module-mirp.settings.general_parameters"], [0, "module-mirp.settings.generic"], [0, "module-mirp.settings.image_processing_parameters"], [0, "module-mirp.settings.interpolation_parameters"], [0, "module-mirp.settings.perturbation_parameters"], [0, "module-mirp.settings.resegmentation_parameters"], [0, "module-mirp.settings.transformation_parameters"], [3, "module-mirp.deep_learning_preprocessing"], [7, "module-mirp.extract_image_parameters"], [11, "module-mirp.extract_mask_labels"]], "deep_learning_preprocessing() (in module mirp.deep_learning_preprocessing)": [[3, "mirp.deep_learning_preprocessing.deep_learning_preprocessing"]], "deep_learning_preprocessing_generator() (in module mirp.deep_learning_preprocessing)": [[3, "mirp.deep_learning_preprocessing.deep_learning_preprocessing_generator"]], "mirp.deep_learning_preprocessing": [[3, "module-mirp.deep_learning_preprocessing"]], "get_data_xml() (in module mirp.utilities.config_utilities)": [[6, "mirp.utilities.config_utilities.get_data_xml"]], "import_image_and_mask() (in module mirp.data_import.import_image_and_mask)": [[6, "mirp.data_import.import_image_and_mask.import_image_and_mask"]], "extract_image_parameters() (in module mirp.extract_image_parameters)": [[7, "mirp.extract_image_parameters.extract_image_parameters"]], "mirp.extract_image_parameters": [[7, "module-mirp.extract_image_parameters"]], "extract_mask_labels() (in module mirp.extract_mask_labels)": [[11, "mirp.extract_mask_labels.extract_mask_labels"]], "mirp.extract_mask_labels": [[11, "module-mirp.extract_mask_labels"]], "extract_features() (in module mirp.extract_features_and_images)": [[12, "mirp.extract_features_and_images.extract_features"]], "extract_features_and_images() (in module mirp.extract_features_and_images)": [[12, "mirp.extract_features_and_images.extract_features_and_images"]], "extract_features_and_images_generator() (in module mirp.extract_features_and_images)": [[12, "mirp.extract_features_and_images.extract_features_and_images_generator"]], "extract_features_generator() (in module mirp.extract_features_and_images)": [[12, "mirp.extract_features_and_images.extract_features_generator"]], "extract_images() (in module mirp.extract_features_and_images)": [[12, "mirp.extract_features_and_images.extract_images"]], "extract_images_generator() (in module mirp.extract_features_and_images)": [[12, "mirp.extract_features_and_images.extract_images_generator"]]}})
\ No newline at end of file
diff --git a/docs/tutorial_apply_image_filter.html b/docs/tutorial_apply_image_filter.html
index cc9be925..a8015f2a 100644
--- a/docs/tutorial_apply_image_filter.html
+++ b/docs/tutorial_apply_image_filter.html
@@ -1,11 +1,11 @@
-
+
- Tutorial: Applying image filters — mirp 2.2.3 documentation
-
+ Tutorial: Applying image filters — mirp 2.2.4 documentation
+
@@ -16,7 +16,7 @@
-
+
@@ -71,7 +71,7 @@
-Deep Dive
+Documentation and API