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Sketch-based Image-independent Editing of 3D Tumor Segmentations using Variational Interpolation. Frank Heckel 1 , Stefan Braunewell 1 , Grzegorz Soza 2 , Christian Tietjen 2 , Horst K. Hahn 1. - PowerPoint PPT Presentation
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© Fraunhofer MEVIS
Frank Heckel1, Stefan Braunewell1, Grzegorz Soza2, Christian Tietjen2, Horst K. Hahn1
Sketch-based Image-independent Editing of 3D Tumor Segmentations using Variational Interpolation
1 Fraunhofer MEVIS, Germany, 2 Siemens AG, Healthcare Sector, Imaging & Therapy Division, Computed Tomography, Germany
© Fraunhofer MEVIS2 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Motivation
Segmentation is one of the essential tasks in medical image analysis Many sophisticated automatic segmentation algorithms exist … … which might fail in some cases (low contrast, noise, biological
variability)
What to do? Manual segmentation? Takes too long Different algorithm? Might fail as well Locally correct the error!
Why do we need efficient segmentation editing tools?Solution Results Outlook Conclusion
© Fraunhofer MEVIS3 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Motivation
Requirements: Intuitive interaction in 2D – estimate the user’s intention in 3D Local modifications Real-time feedback Provide a general tool (for different objects and modalities) Be independent of the preceding automatic algorithm
The user expects the tool to allow him or her to correct all errors With only a few steps!
The segmentation problems are typically hard (noise, low contrast, …) Do not use the image!
What makes segmentation editing a difficult problem?Solution Results Outlook Conclusion
© Fraunhofer MEVIS4 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Solution
Use methods known from object reconstruction Contour-based representation Can be treated as a point cloud Reconstruct a smooth surface using variational interpolation
Segmentation Formulated as an Object Reconstruction Problem
0)()()(1
k
jjj cxwxPxf
Results Outlook Conclusion Motivation
© Fraunhofer MEVIS5 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Solution
Hole-handling: Recursively check the level of embedding Holes have an odd level Invert the sign of the normals
Segmentation Formulated as an Object Reconstruction Problem
without hole-handling
with hole-handling
Results Outlook Conclusion Motivation
© Fraunhofer MEVIS6 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
SolutionSketch-based Editing in 2D
User input Correction result Edited region
Part containing the center of
gravity
Results Outlook Conclusion Motivation
© Fraunhofer MEVIS7 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Solution
We have to deal with imperfection:
Sketch-based Editing in 2Dadd
remov
e
add +
remov
e
replc
ae
Results Outlook Conclusion Motivation
© Fraunhofer MEVIS8 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Solution
A correction might generate new “holes”: Remove all contours whose level of embedding has changed
Sketch-based Editing in 2DResults Outlook Conclusion Motivation
© Fraunhofer MEVIS9 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Solution
Compute a correction depth
Reconstruct the new surfacebetween start and end
3D Extrapolation using Variational Interpolation
𝑠start=max❑
(𝑠−𝑑 (𝐶𝑠𝑢 ) , 𝑠min )
𝑑 (𝐶 𝑠𝑢 )=⌈max
𝑖 {min𝑗 {|𝐶𝑠𝑒 [𝑖 ]−𝐶𝑠𝑢[ 𝑗]|}}𝑑𝑠
⌉
𝑪𝒔𝒖
𝑪𝒔𝒆
𝒔𝐬𝐭𝐚𝐫𝐭
𝒔𝒆𝒏𝒅𝒔
Results Outlook Conclusion Motivation
𝒔
© Fraunhofer MEVIS10 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Solution
Making the correction local: Dilate the edited region
Duplicate it to all slices of the reconstruction Use new segmentation in this region only
3D Extrapolation using Variational Interpolation
𝑘=2 ⌈ 143√ 3𝑛4𝜋 ⌉+1
Sphere volume:→
𝒌
Results Outlook Conclusion Motivation
© Fraunhofer MEVIS11 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
SolutionManual Correction Workflow
Corrections can be performed in any view User can arbitrarily switch between views
Previously performed corrections should be part of the new surface Keep all user-inputs and use them for reconstruction
Results Outlook Conclusion Motivation
user-input(1st step, axial
view) user-input(2nd step, sagittal view)
© Fraunhofer MEVIS12 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
SolutionResults Outlook Conclusion Motivation
© Fraunhofer MEVIS13 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Results
Data: 89 tumors in CT (lung nodules, liver metastases, lymph nodes) Participants: 2 technical experts with 6+ years experience in tumor
segmentation and assessment Qualitative rating of the correction tool
Median: 4 steps (53s), Avg. time per step: 0.4s1
Rating
Meaning # Cases
Percentage
++ Perfect 14 15.7%+ Good 43 47.3%0 Acceptable 25 28.1%- Bad 6 6.7%-- Unacceptable 1 1.1%
1 Intel Xeon X5550 (2.66GHz), 12GB RAM, Windows 7 64-Bit, 4 cores used
Outlook Conclusion Solution
92.1%
© Fraunhofer MEVIS14 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Outlook
Main problem currently: Contradictory user inputs
Reconstruction is currently too slow for large objects (like the liver) Comparison the other methods
Strongly depends on the specific segmentation task and the experience and requirements of the users
Proposal: Segmentation editing challenge
Conclusion Results
© Fraunhofer MEVIS15 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
Conclusion
Segmentation editing is an indispensable step in the segmentation process
Efficient editing in 3D is challenging
Sketching provides an intuitive interface for segmentation editing in 2D
We have proposed a general, efficient editing tool 2D corrections are extrapolated to 3D using object reconstruction Can be used for any 3D modality and any compact object
Outlook
© Fraunhofer MEVIS16 / 15Frank Heckel et al. Sketch-based Image-independent Editing of 3D Tumor
Segmentations28. Sept. 2012
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