Version 7 vs 9
Version 7 vs 9
Content Changes
Content Changes
{icon arrow-left} [[mitk/changelog/2022.17 | Previous changelog]] โข [[mitk/changelog/release-v2022.04 | Next changelog]] {icon arrow-right}
NOTE: This is a release changelog. It is composed of a selected short list of highlights since the last release [[mitk/changelog/release-v2021.10 | MITK v2021.10]] - split into dedicated user and developer sections. See the past four [[mitk/changelog | changelogs]] starting from [[mitk/changelog/2021.48]] for a comprehensive, developer-centric overview of changes.
---
= News for MITK Workbench users =
== Segmentation ==
For MITK v2022.04, we focused mainly on segmentation and we are already excited about your feedback on many improvements and a streamlined segmentation workflow. Highlights include:
- The Segmentation and Multilabel Segmentation Views were finally merged into a single Segmentation View
- Default label names and distinctive colors for new labels further reduce interuptions of your workflow
- Segmentation tools are now more aware of the currently active label and labels in general, providing improved intuitive behavior
- Image registration now support the mapping of multi label segmentations.
- Custom default labels for new segmentations greatly streamline repetitive segmentation tasks
== Introducing nnU-Net in MITK ==
We are happy to officially announce the integration of the fantastic [[https://github.com/MIC-DKFZ/nnunet | nnU-Net]] for fully automatic segmentation tasks. Currently **experimental** and only available in our **Linux** installers, your local nnU-Net Python environment setup can be used in MITK to infer, view and further process segmentation masks seamlessly with other tools. Check out the [[https://docs.mitk.org/2022.04/org_mitk_views_segmentation.html#org_mitk_views_segmentationnnUNetTool | user guide]] for more information.
== ๐ Known issues ==
- DICOM file names/paths with non-ASCII characters (e. g. German umlauts) may fail to load on Windows. Two different workarounds are:
- Rename the file
- Switch to the UTF-8 locale of Windows 10 2019-03 or later before starting the MITK Workbench
- The label highlight in the Segmentation view may get out of sync (highlight in the label list does not reflect the active label). Reason: changing the lock and visibility state of a label, changes the highlight in the label list, but does not change the active label. Workaround: Explicitly select your wished active label after changing visibility or lock states to ensure the right setting.
- Registration evaluator's swipe mode: When using the swipe mode to inspect the registration results, the swip rendering is always one interaction "behind". So it will be rendered with the position you clicked before the current crosshair position.
---
= News for developers =
== ITK v5 upgrade ==
The biggest change in the backend - besides all the work on segmentation - is the major upgrade of ITK, one of our core dependencies, to version 5. While the upgrade will give us some benefits and access to the latest features and algorithms of ITK for upcoming releases, we focused on the migration of existing code for this release to continuously provide a stable and robust user experience with MITK. When you upgrade your code base to MITK v2022.04, you probably need to adapt some code as well. Scan the [[mitk/changelog/2022.12 | previous changelogs]] for more information and examples on how to migrate existing code.
== ๐ Third-party dependency changes ==
NOTE: [[https://docs.mitk.org/2022.04/SupportedPlatformsPage.html | Here]] is the [[https://docs.mitk.org/2022.04/SupportedPlatformsPage.html | list of supported platforms]] for MITK v2022.04.
The following table shows a complete list of changed third-party dependencies.
| Dependency | Old version | New version |
| --- | --- | --- |
| Boost | 1.74 | 1.78 beta 1 |
| ITK | 4.13.3 | 5.2.1 |
| VTK | 9.0.1 | 9.1.0 |
| GDCM | 3.0.8 | 3.0.10 |
| OpenCV | 3.4.8 | 3.4.16 |
| Eigen | 3.2.8 | 3.4.0 |
| JsonCpp | ? | 1.9.5 |
== ๐ฅ API-breaking changes ==
Besides the inevitable API-breaking changes after the [[mitk/changelog/2022.12 | ITK v5]] upgrade, most other minor API-breaking changes are summarized [[mitk/changelog/2022.12 | here]] as well. In addition, some legacy classes and properties in the context of Volume Visualization were removed, as listed in the [[mitk/changelog/2022.17 | previous changelog]].
{icon arrow-left} [[mitk/changelog/2022.17 | Previous changelog]] โข [[mitk/changelog/release-v2022.04 | Next changelog]] {icon arrow-right}
{icon arrow-left} [[mitk/changelog/2022.17 | Previous changelog]] โข [[mitk/changelog/2022.28 | Next changelog]] {icon arrow-right}
NOTE: This is a release changelog. It is composed of a selected short list of highlights since the last release [[mitk/changelog/release-v2021.10 | MITK v2021.10]] - split into dedicated user and developer sections. See the past four [[mitk/changelog | changelogs]] starting from [[mitk/changelog/2021.48]] for a comprehensive, developer-centric overview of changes.
---
= News for MITK Workbench users =
== Segmentation ==
For MITK v2022.04, we focused mainly on segmentation and we are already excited about your feedback on many improvements and a streamlined segmentation workflow. Highlights include:
- The Segmentation and Multilabel Segmentation Views were finally merged into a single Segmentation View
- Default label names and distinctive colors for new labels further reduce interuptions of your workflow
- Segmentation tools are now more aware of the currently active label and labels in general, providing improved intuitive behavior
- Custom default labels for new segmentations greatly streamline repetitive segmentation tasks
- Mapping of multi-label segmentations is now supported by Image Registration
== Introducing nnU-Net in MITK ==
We are happy to officially announce the integration of the fantastic [[https://github.com/MIC-DKFZ/nnunet | nnU-Net]] for fully automatic segmentation tasks. Currently **experimental** and only available in our **Linux** installers, your local nnU-Net Python environment setup can be used in MITK to infer, view and further process segmentation masks seamlessly with other tools. Check out the [[https://docs.mitk.org/2022.04/org_mitk_views_segmentation.html#org_mitk_views_segmentationnnUNetTool | user guide]] for more information.
== ๐ Known issues ==
- DICOM file names/paths with non-ASCII characters (e. g. German umlauts) may fail to load on Windows. Two different workarounds are:
- Rename the file
- Switch to the UTF-8 locale of Windows 10 2019-03 or later before starting the MITK Workbench
- The label highlight in the Segmentation View may get out of sync with the actual active label when changing the lock or visibility state of other labels. Workaround: Explicitly select the active label after changing visibility or lock states of ther labels.
- Registration Evaluator's swipe mode: When using the swipe mode to inspect the registration results, the swipe rendering is always one interaction //behind//. So it will be rendered with the position you clicked before the current crosshair position.
---
= News for developers =
== ITK v5 upgrade ==
The biggest change in the backend - besides all the work on segmentation - is the major upgrade of ITK, one of our core dependencies, to version 5. While the upgrade will give us some benefits and access to the latest features and algorithms of ITK for upcoming releases, we focused on the migration of existing code for this release to continuously provide a stable and robust user experience with MITK. When you upgrade your code base to MITK v2022.04, you probably need to adapt some code as well. Scan the [[mitk/changelog/2022.12 | previous changelogs]] for more information and examples on how to migrate existing code.
== ๐ Third-party dependency changes ==
NOTE: [[https://docs.mitk.org/2022.04/SupportedPlatformsPage.html | Here]] is the [[https://docs.mitk.org/2022.04/SupportedPlatformsPage.html | list of supported platforms]] for MITK v2022.04.
The following table shows a complete list of changed third-party dependencies.
| Dependency | Old version | New version |
| --- | --- | --- |
| Boost | 1.74 | 1.78 beta 1 |
| ITK | 4.13.3 | 5.2.1 |
| VTK | 9.0.1 | 9.1.0 |
| GDCM | 3.0.8 | 3.0.10 |
| OpenCV | 3.4.8 | 3.4.16 |
| Eigen | 3.2.8 | 3.4.0 |
| JsonCpp | ? | 1.9.5 |
== ๐ฅ API-breaking changes ==
Besides the inevitable API-breaking changes after the [[mitk/changelog/2022.12 | ITK v5]] upgrade, most other minor API-breaking changes are summarized [[mitk/changelog/2022.12 | here]] as well. In addition, some legacy classes and properties in the context of Volume Visualization were removed, as listed in the [[mitk/changelog/2022.17 | previous changelog]].
{icon arrow-left} [[mitk/changelog/2022.17 | Previous changelog]] โข [[mitk/changelog/2022.28 | Next changelog]] {icon arrow-right}
{icon arrow-left} [[mitk/changelog/2022.17 | Previous changelog]] โข [[mitk/changelog/release-v2022.0428 | Next changelog]] {icon arrow-right}
NOTE: This is a release changelog. It is composed of a selected short list of highlights since the last release [[mitk/changelog/release-v2021.10 | MITK v2021.10]] - split into dedicated user and developer sections. See the past four [[mitk/changelog | changelogs]] starting from [[mitk/changelog/2021.48]] for a comprehensive, developer-centric overview of changes.
---
= News for MITK Workbench users =
== Segmentation ==
For MITK v2022.04, we focused mainly on segmentation and we are already excited about your feedback on many improvements and a streamlined segmentation workflow. Highlights include:
- The Segmentation and Multilabel Segmentation Views were finally merged into a single Segmentation View
- Default label names and distinctive colors for new labels further reduce interuptions of your workflow
- Segmentation tools are now more aware of the currently active label and labels in general, providing improved intuitive behavior
- Image registration now support the mapping of multi label segmentations.
- Custom default labels for new segmentations greatly streamline repetitive segmentation tasks
- Mapping of multi-label segmentations is now supported by Image Registration
== Introducing nnU-Net in MITK ==
We are happy to officially announce the integration of the fantastic [[https://github.com/MIC-DKFZ/nnunet | nnU-Net]] for fully automatic segmentation tasks. Currently **experimental** and only available in our **Linux** installers, your local nnU-Net Python environment setup can be used in MITK to infer, view and further process segmentation masks seamlessly with other tools. Check out the [[https://docs.mitk.org/2022.04/org_mitk_views_segmentation.html#org_mitk_views_segmentationnnUNetTool | user guide]] for more information.
== ๐ Known issues ==
- DICOM file names/paths with non-ASCII characters (e. g. German umlauts) may fail to load on Windows. Two different workarounds are:
- Rename the file
- Switch to the UTF-8 locale of Windows 10 2019-03 or later before starting the MITK Workbench
- The label highlight in the Segmentation viewView may get out of sync (highlight in the label list does not reflect the active label). Reason: changing the lock and visibility state of a label, changes the highlight in the label list, but does not change the active labelwith the actual active label when changing the lock or visibility state of other labels. Workaround: Explicitly select your wishedthe active label after changing visibility or lock states to ensureof the right settingr labels.
- Registration eEvaluator's swipe mode: When using the swipe mode to inspect the registration results, the swipe rendering is always one interaction "//behind"//. So it will be rendered with the position you clicked before the current crosshair position.
---
= News for developers =
== ITK v5 upgrade ==
The biggest change in the backend - besides all the work on segmentation - is the major upgrade of ITK, one of our core dependencies, to version 5. While the upgrade will give us some benefits and access to the latest features and algorithms of ITK for upcoming releases, we focused on the migration of existing code for this release to continuously provide a stable and robust user experience with MITK. When you upgrade your code base to MITK v2022.04, you probably need to adapt some code as well. Scan the [[mitk/changelog/2022.12 | previous changelogs]] for more information and examples on how to migrate existing code.
== ๐ Third-party dependency changes ==
NOTE: [[https://docs.mitk.org/2022.04/SupportedPlatformsPage.html | Here]] is the [[https://docs.mitk.org/2022.04/SupportedPlatformsPage.html | list of supported platforms]] for MITK v2022.04.
The following table shows a complete list of changed third-party dependencies.
| Dependency | Old version | New version |
| --- | --- | --- |
| Boost | 1.74 | 1.78 beta 1 |
| ITK | 4.13.3 | 5.2.1 |
| VTK | 9.0.1 | 9.1.0 |
| GDCM | 3.0.8 | 3.0.10 |
| OpenCV | 3.4.8 | 3.4.16 |
| Eigen | 3.2.8 | 3.4.0 |
| JsonCpp | ? | 1.9.5 |
== ๐ฅ API-breaking changes ==
Besides the inevitable API-breaking changes after the [[mitk/changelog/2022.12 | ITK v5]] upgrade, most other minor API-breaking changes are summarized [[mitk/changelog/2022.12 | here]] as well. In addition, some legacy classes and properties in the context of Volume Visualization were removed, as listed in the [[mitk/changelog/2022.17 | previous changelog]].
{icon arrow-left} [[mitk/changelog/2022.17 | Previous changelog]] โข [[mitk/changelog/release-v2022.0428 | Next changelog]] {icon arrow-right}