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- Csaba Pinter (Queen's University, Canada)
Till Best- Nikos Makris (Brigham and Women's Hospital and Harvard Medical School, USA)
- Filippo Cicali (Massachusetts General Hospital and Harvard Medical School, USA)
- Tina Kapur (Brigham and Women’s Hospital and Harvard Medical School, USA)
- Marco Nolden (DKFZ, Germany)
- Attila Nagy (SZTE Medical School, Hungary)
- Sharon Peled (Brigham and Women's Hospital and Harvard Medical School, USA)
- Segment Editor is the new manual and semi-automated image segmentation module in Slicer. It has powerful tools, but the learning curve can be steep for segmenting more complex cases.
- The objective is to help researchers aiming to use Segment Edtitor use it for their specific use cases, and augment the training material based on the results
- Each participating researcher brings a dataset, for which we'll attempt to develop an effective segmentation workflow
- Add the developed workflows in the Slicer Segmentation Recipes page
- Publicly share dataset
- Create a tutorial page for the segmentation case including screenshots
- Insula segmentation in MRI with Filippo Cicali and Nikos Makris
- Possible solution: Use Grow from seeds iteratively, then use scissors and masked paint to cut
- Consider speeding up segmentation by using a stylus instead of a mouse, and explore faster ways of slice navigation (3D mouse, webcam tracking, etc?)
- Brachytherapy needle segmentation in MRI for training deep learning models
- Possible solution: Add "tube" mode from Markups to Models extension to Segment Editor, as an option to surface cut or a new effect in a new extension
- Deep learning training support: need cohort segmentation slicelet that allows configuring segment editor before segmenting first patient for simpler, less distracting user interface for easier usage and smoother and more reliable segmentation workflow
- Minor help to multiple projects involving segmentation
Whole heart segmentation:
Spine phantom 3D printing:
Segment Editor in presentation in Casa África: