Mapping between MR brain images and a voxel model

Jin, Zhang; Mowforth, P.

doi:10.3109/14639239109012126

Cited by 10 publications

(7 citation statements)

References 4 publications

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“…However, here we have a 2D to 3D matching problem involving the collective alignment of slices within a volume space. Unlike previous work on slice to volume matching in medical imaging, where individual slices from an interventional MRI study (95), postmortem study (96), anatomical atlas (97), or functional MRI study (98) are matched to a full 3D volume acquired separately, here we do not have a reference 3D volume.…”

Section: A Hybrid Solution To 3d Fetal Mri: Computer Vision Meets Mmentioning

confidence: 99%

Mapping Fetal Brain Development In Utero Using Magnetic Resonance Imaging: The Big Bang of Brain Mapping

Studholme

2011

Annu. Rev. Biomed. Eng.

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The development of tools to construct and investigate probabilistic maps of the adult human brain from MRI have led to advances in both basic neuroscience and clinical diagnosis. These tools are increasingly being applied to brain development in adolescence, childhood and even neonatal and premature neonatal imaging. Looking even earlier in development, parallel developments in clinical fetal Magnetic Resonance Imaging (MRI) have led to its growing use as a tool in challenging medical conditions. This has motivated new engineering developments that combine optimal fast MRI scans with techniques derived from computer vision that allow full 3D imaging of the moving fetal brain in utero without sedation. These promise to provide a new and unprecedented window into early human brain growth. This article will review the developments that have led us to this point, and examine the current state of the art in the fields of fast fetal imaging, motion correction and the tools to analyze dynamically changing fetal brain structure. New methods to deal with developmental tissue segmentation and the construction of spatio-temporal atlases will be examined, together with techniques to map fetal brain growth patterns.

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Section: A Hybrid Solution To 3d Fetal Mri: Computer Vision Meets Mmentioning

confidence: 99%

Mapping Fetal Brain Development In Utero Using Magnetic Resonance Imaging: The Big Bang of Brain Mapping

Studholme

2011

Annu. Rev. Biomed. Eng.

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“…In previously published reports, SV registration was mainly applied to the brain for applications of functional MRI, 9,10 postmortem pathology studies, 11 and anatomical modeling. 12 There are no reports of SV registration for abdominal organs or iMRI guidance.…”

Section: Introductionmentioning

confidence: 99%

Automatic 3D registration for interventional MRI-guided treatment of prostate cancer

Fei

Duerk

Wilson

2002

Comput. Aided Surg.

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The goal of this research is to register real-time interventional magnetic resonance imaging (iMRI) slice images with a previously obtained high-resolution MRI image volume, which in turn can be registered with functional images such as those from SPECT. The immediate application is in iMRI-guided treatment of prostate cancer, where additional images are desired to improve tumor targeting. In this article, simulation experiments are performed to demonstrate the feasibility of slice-to-volume registration for this application. We acquired 3D volume images from a 1.5-T MRI system and simulated low-field iMRI image slices by creating thick slices and adding noise. We created a slice-to-volume mutual information registration algorithm with special features to improve robustness. Features included a multiresolution approach, two similarity measures, and automatic restarting to avoid local minima. To assess the quality of registration, we calculated 3D displacements on a voxel-by-voxel basis over a volume of interest between slice-to-volume registration and volume-to-volume registration, which was previously shown to be quite accurate. More than 800 registration experiments were performed on MR images of three volunteers. The slice-to-volume registration algorithm was very robust and accurate for transverse slice images covering the prostate, with a registration error of only 0.4 +/- 0.2 mm. Error was greater at other slice orientations and positions. The automatic slice-to-volume mutual information registration algorithm is robust and probably sufficiently accurate to aid in iMRI-guided treatment of prostate cancer.

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“…4,5,6 Previously reported methods on slice to volume registration were mainly applied to the brain. 7,8,9 For the case of volume to volume registration, there are many reports of accurate voxel-based registration in the brain 10,11,12,13 and abdominal and pelvic organs. There are challenges to successful slice to volume registration for the prostate.…”

Section: Introductionmentioning

confidence: 99%

<title>Robust registration method for interventional MRI-guided thermal ablation of prostate cancer</title>

Fei¹,

Wheaton²,

Lee³

et al. 2001

SPIE Proceedings

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We are investigating methods to register live-time interventional magnetic resonance imaging (iMRI) slice images with a previously obtained, high resolution MRI image volume. The immediate application is for iMRI-guided treatments of prostate cancer. We created and evaluated a slice-to-volume mutual information registration algorithm for MR images with special features to improve robustness. Features included a multi-resolution approach and automatic restarting to avoid local minima. We acquired 3D volume images from a 1.5 T MRI system and simulated iMRI images. To assess the quality of registration, we calculated 3D displacement on a voxel-by-voxel basis over a volume of interest between slice-to-volume registration and volume-to-volume registrations that were previously shown to be quite accurate. More than 500 registration experiments were performed on MR images of volunteers. The slice-to-volume registration algorithm was very robust for transverse slice images covering the prostate. A 100% success rate was achieved with an acceptance criterion of < 1.0 mm displacement error over the prostate. Our automatic slice-to-volume mutual information registration algorithm is robust and probably sufficiently accurate to aid in the application of iMRI-guided thermal ablation of prostate cancer.

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Mapping between MR brain images and a voxel model

Cited by 10 publications

References 4 publications

Mapping Fetal Brain Development In Utero Using Magnetic Resonance Imaging: The Big Bang of Brain Mapping

Mapping Fetal Brain Development In Utero Using Magnetic Resonance Imaging: The Big Bang of Brain Mapping

Automatic 3D registration for interventional MRI-guided treatment of prostate cancer

<title>Robust registration method for interventional MRI-guided thermal ablation of prostate cancer</title>

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