automatic cochlea multi-modal images segmentation · 2018-04-03 · automatic cochlea multi-modal...
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Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Automatic Cochlea Multi-modal Images Segmentation Using Adaptive Stochastic Gradient Descent
Ibraheem Al-Dhamari, Sabine Bauer, Roland Jacob and Dietrich Paulus
Active Vision Group
Institute of Medical Technology and Information Processing
March 2018
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Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Disclosure
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There is no relevant conflict of interest related to this presentation.
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Introduction: Problem Definition
- A practical technique to get cochlea segmentation from medical images is needed.
- Doctors need cochlea measurement before the surgery to select the best implant for a patient.
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Image source: Blausen.com staff (2014). "Medical gallery of Blausen Medical 2014". WikiJournal of Medicine
- Medical image analysis based on well segmented cochlea may provide these measurements.
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Introduction: Cochlea Segmentation
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Input image Segmentation
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Introduction: Cochlea Segmentation Challenges
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- Low resolution images, the best spacing we have is [0.125, 0.125, 0.50] mm for CBCT.
- Cochlea is a small organ with a complicated structure. Cochlea scalas are not visible in the clinical images.
- Different types of images CT, MRI and CBCT.
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Methods: Adaptive Stochastic Gradient Descent
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- An optimizer for medical image registration proposed by Klein et al [1].
[1] Klein et al: Adaptive stochastic gradient descent optimisation for image registration. International Journal of Computer Vision, 81(3):227-239,(2009).
- We used it in our method ACIR [2] to solve the problem of cochlea multi-modal image registration and fusion.
[2] Ibraheem Al-Dhamari et al, ACIR: automatic cochlea image registration. Proceedings of SPIE Medical Imaging 2017, Image Processing. 2017;10133(10):47–67.
- The proposed method is to use ACIR in an model-atlas-based segmentation to solve the problem of cochlea segmentation.
CBCT-CT MR-CT CBCTb-CTBCTa
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Methods: Adaptive Stochastic Gradient Descent
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- ASGD is implemented in elastix, a standard medical image registration tool,[3] which is available as a public open-source.
[3] http://elastix.isi.uu.nl
- ACIR and this work are implemented as 3D Slicer, a standard medical image processing tool, [4] plugins which is also available as a public open-source.
[4] https://www.slicer.org
CBCT-CT MR-CT CBCTb-CTBCTa
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Methods: Cochlea Atlas-based Segmentation
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Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Methods: Cochlea Model
9 [5] Gerber et al, A multiscale imaging and modelling dataset of the human inner ear, Scientific Data 4, 170132 (2017).
- A high resolution mCT cochlea image from a public dataset [5] is prepared and used.
- The mCT segmentation is registered to a clinical cochlea image. - The cochlea clinical image and its segmentation are used as a model.
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Methods: Cochlea Model
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- A high resolution mCT cochlea image from a public dataset [5] is prepared and used.
- The mCT segmentation is registered to a clinical cochlea image. - The cochlea clinical image and its segmentation are used as a model.
[5] Gerber et al, A multiscale imaging and modelling dataset of the human inner ear, Scientific Data 4, 170132 (2017).
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Sample results
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CBCT MRI CT
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018
Conclusion
- A model-atlas-based method for automatic cochlea multi-modal image segmentation is proposed.
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- The proposed method segments a cochlea clinical image and generates a 3d model in less than 3 seconds.
- Using higher resolution histology model may provide better segmentation.
Automatic Cochlea Multi-modal Images Segmentation
Al-Dhamari, CI2018 13
Thanks