Intersection based registration of slice stacks to form 3D images of the human fetal brain

Kim, K.; Hansen, Mark F.; Habas, Piotr A.; Rousseau, François; Glenn, Orit A.; Barkovich, A. James; Studholme, Colin

doi:10.1109/isbi.2008.4541209

Cited by 13 publications

(18 citation statements)

References 11 publications

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“…Recent studies on human brain development of fetuses using 2D MR slices can be found in [13]–[15]. The first automated tissue segmentation of developing tissues from motion corrected un-sedated fetal brain anatomy was recently described in utero [16] following the development of 3D reconstruction techniques [17]–[19]. …”

Section: Introductionmentioning

confidence: 99%

Intersection Based Motion Correction of Multislice MRI for 3-D in Utero Fetal Brain Image Formation

Kim

Habas

Rousseau

et al. 2010

IEEE Trans. Med. Imaging

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In recent years post-processing of fast multi-slice MR imaging to correct fetal motion has provided the first true 3D MR images of the developing human brain in utero. Early approaches have used reconstruction based algorithms, employing a two step iterative process, where slices from the acquired data are re-aligned to an approximate 3D reconstruction of the fetal brain, which is then refined further using the improved slice alignment. This two step slice-to-volume process, although powerful, is computationally expensive in needing a 3D reconstruction, and is limited in its ability to recover sub-voxel alignment. Here, we describe an alternative approach which we term slice intersection motion correction (SIMC), that seeks to directly co-align multiple slice stacks by considering the matching structure along all intersecting slice pairs in all orthogonally planned slices that are acquired in clinical imaging studies. A collective update scheme for all slices is then derived, to simultaneously drive slices into a consistent match along their lines of intersection. We then describe a 3D reconstruction algorithm that, using the final motion corrected slice locations, suppresses through-plane partial volume effects to provide a single high isotropic resolution 3D image. The method is tested on simulated data with known motions and is applied to retrospectively reconstruct 3D images from a range of clinically acquired imaging studies. The quantitative evaluation of the registration accuracy for the simulated data sets demonstrated a significant improvement over previous approaches. An initial application of the technique to studying clinical pathology is included, where the proposed method recovered up to 15 mm of translation and 30 degrees of rotation for individual slices, and produced full 3D reconstructions containing clinically useful additional information not visible in the original 2D slices.

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Section: Introductionmentioning

confidence: 99%

Intersection Based Motion Correction of Multislice MRI for 3-D in Utero Fetal Brain Image Formation

Kim

Habas

Rousseau

et al. 2010

IEEE Trans. Med. Imaging

Self Cite

161

173

View full text Add to dashboard Cite

show abstract

“…Here we employ Slice Intersection Motion Correction [15,16] to estimate individual slice motion. This approach, in effect, extends 2D image mosaicing to the extreme case of considering overlap at the intersection of any pairs of slices that have been acquired in approximately orthogonal orientations.…”

Section: Methodsmentioning

confidence: 99%

Imaging and shape analysis of the moving human fetal brain in-utero

Studholme

2010

2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers

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This paper examines new techniques that allow the formation and analysis of high resolution 3D MR images of the developing human fetal brain in utero, by carrying out object based motion correction of multi-slice MR images of the moving fetal head within deforming maternal tissues. The approaches combine modern fast snapshot slice imaging with techniques derived from computer vision to retrospectively estimate motion of regions within each slice corresponding to the fetal head. The paper specifically examines the problem of reconstructing volume images in cases of highly motion scattered slices where the density of the image data is highly variable. Voxel density maps are calculated and the reconstruction evaluated. Examples are included reconstructing full 3D image volumes from typical multi-slice clinical imaging data.

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“…The MR sequence parameters (TR = 4000–8000ms, TE = 91ms) were originally designed for clinical scans and cannot be adjusted for image analysis purposes. After acquisition, image stacks are registered using an intersection-based technique [7] to account for spontaneous fetal movement during scanning and reconstructed into 3D volumes with isotropic resolution 0.469mm × 0.469mm × 0.469mm. Reconstructed volumes are manually segmented into regions of cortical grey matter (GM), white matter (WM), the germinal matrix (GMAT) and ventricles (VENT).…”

Section: Methodsmentioning

confidence: 99%

A Spatio-temporal Atlas of the Human Fetal Brain with Application to Tissue Segmentation

Habas

Kim

Rousseau

et al. 2009

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

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Abstract. Modeling and analysis of MR images of the early developing human brain is a challenge because of the transient nature of different tissue classes during brain growth. To address this issue, a statistical model that can capture the spatial variation of structures over time is needed. Here, we present an approach to building a spatio-temporal model of tissue distribution in the developing brain which can incorporate both developed tissues as well as transient tissue classes such as the germinal matrix by using constrained higher order polynomial models. This spatiotemporal model is created from a set of manual segmentations through groupwise registration and voxelwise non-linear modeling of tissue class membership, that allows us to represent the appearance as well as disappearance of the transient brain structures over time. Applying this model to atlas-based segmentation, we generate age-specific tissue probability maps and use them to initialize an EM segmentation of the fetal brain tissues. The approach is evaluated using clinical MR images of young fetuses with gestational ages ranging from 20.57 to 24.71 weeks. Results indicate improvement in performance of atlas-based EM segmentation provided by higher order temporal models that capture the variation of tissue occurrence over time.

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Intersection based registration of slice stacks to form 3D images of the human fetal brain

Cited by 13 publications

References 11 publications

Intersection Based Motion Correction of Multislice MRI for 3-D in Utero Fetal Brain Image Formation

Intersection Based Motion Correction of Multislice MRI for 3-D in Utero Fetal Brain Image Formation

Imaging and shape analysis of the moving human fetal brain in-utero

A Spatio-temporal Atlas of the Human Fetal Brain with Application to Tissue Segmentation

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