Non-rigid image registration of brain magnetic resonance images using graph-cuts

So, Ronald W. K.; Tang, Tommy; Chung, Albert C. S.

doi:10.1016/j.patcog.2011.04.008

Cited by 43 publications

(19 citation statements)

References 30 publications

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“…In terms of non-rigid methods, several techiniques have been used in medical image registration. Those consist of thin-plate spline [4], free-form deformations using B-splines [5-8], elastic models [9], fluid models [10-13], and Markov random field approaches [14-16]. …”

Section: Introductionmentioning

confidence: 99%

Multimodal image registration of the scoliotic torso for surgical planning

2013

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BackgroundThis paper presents a method that registers MRIs acquired in prone position, with surface topography (TP) and X-ray reconstructions acquired in standing position, in order to obtain a 3D representation of a human torso incorporating the external surface, bone structures, and soft tissues.MethodsTP and X-ray data are registered using landmarks. Bone structures are used to register each MRI slice using an articulated model, and the soft tissue is confined to the volume delimited by the trunk and bone surfaces using a constrained thin-plate spline.ResultsThe method is tested on 3 pre-surgical patients with scoliosis and shows a significant improvement, qualitatively and using the Dice similarity coefficient, in fitting the MRI into the standing patient model when compared to rigid and articulated model registration. The determinant of the Jacobian of the registration deformation shows higher variations in the deformation in areas closer to the surface of the torso.ConclusionsThe novel, resulting 3D full torso model can provide a more complete representation of patient geometry to be incorporated in surgical simulators under development that aim at predicting the effect of scoliosis surgery on the external appearance of the patient’s torso.

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Section: Introductionmentioning

confidence: 99%

Multimodal image registration of the scoliotic torso for surgical planning

2013

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“…We extend this discrete second order smoothness term for use in a group-wise setting. Alpha expansion has also been effectively used to perform traditional pair-wise registration in So et al (2011), where their contribution outperformed the diffeomorphic demons algorithm found in the Insight Toolkit, as well as other discrete approaches such as Glocker et al (2008). Their idea was to perform alpha expansion using a set of displacement labels.…”

Section: Introduction and Prior Workmentioning

confidence: 99%

A Markov random field approach to group-wise registration/mosaicing with application to ultrasound

Kutarnia

Pedersen

2015

Medical Image Analysis

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“…14,33 The lung overlap error accounts for a coarse registration performance evaluation metric, 32 which however has been commonly used. 11,34,35 Finally, the determinant of Jacobian matrix of the deformation field is used to detect singularities of deformation fields. 20,22,36,37 Quantitative evaluation of image registration using clinical data is susceptible to both algorithm and intrinsic image data variability.…”

Section: Introductionmentioning

confidence: 99%

Selecting registration schemes in case of interstitial lung disease follow‐up in CT

et al. 2015

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Selected registration schemes in case of ILD CT follow-up analysis indicate the significance of adaptive stochastic gradient descent optimizer, as well as the importance of combined rigid and nonrigid schemes providing high accuracy and time efficiency. The selected optimal deformable registration schemes are equivalent in terms of their accuracy and thus compatible in terms of their clinical outcome.

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Non-rigid image registration of brain magnetic resonance images using graph-cuts

Cited by 43 publications

References 30 publications

Multimodal image registration of the scoliotic torso for surgical planning

Multimodal image registration of the scoliotic torso for surgical planning

A Markov random field approach to group-wise registration/mosaicing with application to ultrasound

Selecting registration schemes in case of interstitial lung disease follow‐up in CT

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