3D vertebrae segmentation using graph cuts with shape prior constraints

Aslan, Melih S.; Ali, Asem; Chen, Dongqing; Arnold, Ben; Farag, Aly A.; Xiang, Ping

doi:10.1109/icip.2010.5652849

Cited by 22 publications

(15 citation statements)

References 14 publications

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“…D p (f p ) = − log P (I p | f p ) is formulated to represent the regional properties of segments. V (f p , f q ) is the pairwise interaction model which represents the penalty for the discontinuity between voxels p and q (see [3,12] for more details).…”

Section: Statistical Segmentation Approachmentioning

confidence: 99%

“…3(b). More details on the construction of the shape prior can be read in [3]. The shape prior is registered to the initially segmented image as described in section 2.3.…”

Section: D Shape Prior Reconstruction (Offline)mentioning

confidence: 99%

“…Our general objective is to segment the VBs correctly and increase the accuracy of the BMD measurements and fracture analysis. In this paper, we refer some points to our previous publications [2,3] to conserve space and focus on new ideas.…”

Section: Introductionmentioning

confidence: 99%

“…Doctors need the BMD measurements of vertebral bodies in order to diagnose and treat osteoporosis. The BMD measurements are restricted to the VBs (see [1,2,3] for regions of a vertebrae). The spine bone consists of the vertebral body (VB) and spinal processes.…”

Section: Introductionmentioning

confidence: 99%

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A new segmentation and registration approach for vertebral body analysis

Aslan

Ali

Farag

et al. 2011

2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro

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To diagnose the osteoporosis accurately, the bone mineral density (BMD) measurements of the vertebral bodies (VBs) are required. In this paper, we propose a new segmentation and registration method in order to assist the BMD measurements and fracture analysis (FA) accurately. In this experiment, image appearance and shape information of VBs are used. Our shape model is required to be registered to the testing image to avoid user interaction(s). Our proposed framework has four phases: i) the detection of vertebral body (VB) using the Matched filter, ii) initial segmentation using the intensity and spatial interaction models, iii) the registration of the shape prior and initially segmented image by matching a vector distance function (VDF), and iv) final segmentation using graph cuts which integrates intensity, spatial interaction and shape prior. Preliminary results show that our new algorithm is very promising and can solve many segmentation and registration problems.Index Terms-Vertebral dody (VB), shape based segmentation and registration, BMD measurements.

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Section: Statistical Segmentation Approachmentioning

confidence: 99%

“…3(b). More details on the construction of the shape prior can be read in [3]. The shape prior is registered to the initially segmented image as described in section 2.3.…”

Section: D Shape Prior Reconstruction (Offline)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A new segmentation and registration approach for vertebral body analysis

Aslan

Ali

Farag

et al. 2011

2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro

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“…In 3D methods, image segmentation is usually formulated as classification of voxels into different groups [4], [5], which constitute different segments, or identifying the surfaces that separate different segments [6]. There are several issues when applying 3D methods for material image segmentation.…”

mentioning

confidence: 99%

3D Materials Image Segmentation by 2D Propagation: A Graph-Cut Approach Considering Homomorphism

Waggoner

Zhou

Simmons

et al. 2013

IEEE Trans. on Image Process.

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Segmentation propagation, similar to tracking, is the problem of transferring a segmentation of an image to a neighboring image in a sequence. This problem is of particular importance to materials science, where the accurate segmentation of a series of 2D serial-sectioned images of multiple, contiguous 3D structures has important applications. Such structures may have distinct shape, appearance, and topology, which can be considered to improve segmentation accuracy. For example, some materials images may have structures with a specific shape or appearance in each serial section slice, which only changes minimally from slice to slice, and some materials may exhibit specific inter-structure topology that constrains their neighboring relations. Some of these properties have been individually incorporated to segment specific materials images in prior work. In this paper, we develop a propagation framework for materials image segmentation where each propagation is formulated as an optimal labeling problem that can be efficiently solved using the graph-cut algorithm. Our framework makes three key contributions: 1) a homomorphic propagation approach, which considers the consistency of region adjacency in the propagation; 2) incorporation of shape and appearance consistency in the propagation; and 3) a local non-homomorphism strategy to handle newly appearing and disappearing substructures during this propagation. To show the effectiveness of our framework, we conduct experiments on various 3D materials images, and compare the performance against several existing image segmentation methods.

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An Analysis by Synthesis Approach for Automatic Vertebral Shape Identification in Clinical QCT

Reinhold

Damm

Huber

et al. 2019

Lecture Notes in Computer Science

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Quantitative computed tomography (QCT) is a widely used tool for osteoporosis diagnosis and monitoring. The assessment of cortical markers like cortical bone mineral density (BMD) and thickness is a demanding task, mainly because of the limited spatial resolution of QCT. We propose a direct model based method to automatically identify the surface through the center of the cortex of human vertebra. We develop a statistical bone model and analyze its probability distribution after the imaging process. Using an as-rigid-as-possible deformation we find the cortical surface that maximizes the likelihood of our model given the input volume. Using the European Spine Phantom (ESP) and a high resolution µCT scan of a cadaveric vertebra, we show that the proposed method is able to accurately identify the real center of cortex ex-vivo. To demonstrate the in-vivo applicability of our method we use manually obtained surfaces for comparison.

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3D vertebrae segmentation using graph cuts with shape prior constraints

Cited by 22 publications

References 14 publications

A new segmentation and registration approach for vertebral body analysis

A new segmentation and registration approach for vertebral body analysis

3D Materials Image Segmentation by 2D Propagation: A Graph-Cut Approach Considering Homomorphism

An Analysis by Synthesis Approach for Automatic Vertebral Shape Identification in Clinical QCT

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