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2019 | OriginalPaper | Buchkapitel

Intervertebral Disc Segmentation Using Mathematical Morphology—A CNN-Free Approach

verfasst von : Edwin Carlinet, Thierry Géraud

Erschienen in: Computational Methods and Clinical Applications for Spine Imaging

Verlag: Springer International Publishing

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Abstract

In the context of the challenge of “automatic InterVertebral Disc (IVD) localization and segmentation from 3D multi-modality MR images” that took place at MICCAI 2018, we have proposed a segmentation method based on simple image processing operators. Most of these operators come from the mathematical morphology framework. Driven by some prior knowledge on IVDs (basic information about their shape and the distance between them), and on their contrast in the different modalities, we were able to segment correctly almost every IVD. The most interesting feature of our method is to rely on the morphological structure called the Three of Shapes, which is another way to represent the image contents. This structure arranges all the connected components of an image obtained by thresholding into a tree, where each node represents a particular region. Such structure is actually powerful and versatile for pattern recognition tasks in medical imaging.

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Vorheriges Kapitel Towards a Deformable Multi-surface Approach to Ligamentous Spine Models for Predictive Simulation-Based Scoliosis Surgery Planning

Nächstes Kapitel Deep Learning Framework for Fully Automated Intervertebral Disc Localization and Segmentation from Multi-modality MR Images

Site of the challenge: https://ivdm3seg.weebly.com/.

Topological reminder: In 2D, the cavity-fill-in operator is also called hole filling; in 3D, a cavity is just like a bubble within a sphere (whereas a hole is like a tunnel going through a sphere).

Such a multi-variate version of the tree of shapes is used in the illustrations of Figs. 3 and 4, but not in the segmentation method presented in this paper.

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Titel: Intervertebral Disc Segmentation Using Mathematical Morphology—A CNN-Free Approach
verfasst von: Edwin Carlinet
Thierry Géraud
Verlag: Springer International Publishing
Buch: Computational Methods and Clinical Applications for Spine Imaging
Print ISBN: 978-3-030-13735-9

Electronic ISBN: 978-3-030-13736-6

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-13736-6_9

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