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

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

doi:10.1109/tmi.2009.2030679

Cited by 159 publications

(182 citation statements)

References 26 publications

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“…This is often not correct, which results in the production of sequences that are not in the natural orthogonal planes and not useful diagnostically so the table occupancy for the pregnant female is increased. Sophisticated strategies have been developed to use those wasted images to reconstruct a 3D data set in order to post-process high-quality images in the orthogonal planes [10,11]. In this paper, however, we have applied a FIESTA sequence that allows true 3D acquisitions of the foetal brain in scan times of approximately 40 s. We used a partition thickness of 2.5 mm to reduce partial volume effects while maintaining the good high SNR.…”

Section: Discussionmentioning

confidence: 99%

MRI of the foetal brain using a rapid 3D steady-state sequence

Griffiths¹,

Jarvis²,

McQuillan³

et al. 2013

BJR

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of the foetal brain using a rapid 3D steady-state sequence. Br J Radiol 2013;86:20130168. FULL PAPER MRI of the foetal brain using a rapid 3D steady-state sequence P D GRIFFITHS, PhD Objective: To evaluate the capacity of a rapid T 2 weighted three-dimensional (3D) sequence to diagnose foetal brain abnormalities by comparing the results with current twodimensional (2D) methods. We have also made assessments of the estimates of energy deposition using those methods. Methods: 50 pregnant females were included in this study under the guidance of the institutional review board. All their foetuses had suspected brain abnormalities on antenatal ultrasonography or were at increased risk of a brain malformation based on the results of an earlier pregnancy. All the foetuses had a routine MR protocol that includes three orthogonal plane single-shot fast-spin echoes and 2D steady-state sequences. In addition, a 3D rapid steady-state sequence of the foetal brain was performed (acquisition time approximately 40 s), and the standard and 3D sequences were reported independently and the results were compared. The specific absorption rate (SAR) predicted by the scanner was recorded in 12 cases in order to estimate the energy deposited by the three sequences. Results: The 3D rapid steady-state sequences produced diagnostic-quality images in 41/50 (82%) cases. All the failures were in second trimester foetuses (9/26-35% failure rate). There was a discrepancy between the standard report and findings using the 3D sequence in 2/41 of the foetuses with good-quality 3D imaging. The predicted SAR deposition of the 3D steady-state sequences was comparable with the single-shot fast-spin echo sequence. Conclusion: Our initial assessments of a 3D rapid steadystate sequence to image the foetus are encouraging in terms of diagnostic information and acceptable energy deposition values. The high failure rate in second trimester foetuses probably relates to the greater mobility of the smaller foetuses, and improvements in the 3D sequence are required in terms of reduced acquisition time and higher resolution. Advances in knowledge:We have shown that 3D T 2 weighted images of the foetal brain can be acquired in a clinical setting and produce diagnostic-quality imaging in a high proportion of cases. The success rate in acquiring diagnostic-quality images is related to gestational age. Good-quality images were obtained in all third trimester foetuses but only in approximately two-thirds of second trimester foetuses. This probably reflects the problem of the greater mobility of second trimester foetuses. 3D T 2 weighted acquisitions have great potential for improving the antenatal diagnosis of foetal brain abnormalities and may reduce the time that a pregnant female needs to spend on the MR scanner.MRI of the foetus while in utero (iuMR) has become a valuable adjunct to antenatal ultrasonography over the past 10-15 years, particularly in cases of suspected brain pathology [1][2][3][4][5][6]. The most common approach to iuMR is to use sectional u...

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Section: Discussionmentioning

confidence: 99%

MRI of the foetal brain using a rapid 3D steady-state sequence

Griffiths¹,

Jarvis²,

McQuillan³

et al. 2013

BJR

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“…The most common approach is slice-to-volume registration, where slices are iteratively registered to an estimation of the reconstructed 3D volume (Rousseau et al, 2006;Jiang et al, 2007;Gholipour et al, 2010;Kuklisova-Murgasova et al, 2012). Another approach proposed by Kim et al (2010) formulates the motion correction problem as the optimization of the intersections of all slice pairs from all orthogonally planned scans. A comprehensive overview of these methods is given in Studholme and Rousseau (2013).…”

Section: Motion Correction Of the Fetal Headmentioning

confidence: 99%

“…Down-sampling the target volume followed by up-sampling the mask can be performed to save time during the manual segmentation. In Kim et al (2010), a box around the brain is manually cropped in one stack and propagated to the other stacks after volume-to-volume registration. An ellipsoidal mask, which evolves while the slices are aligned is then used throughout the motion correction procedure.…”

Section: Motion Correction Of the Fetal Headmentioning

confidence: 99%

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Automated fetal brain segmentation from 2D MRI slices for motion correction

et al. 2014

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Motion correction is a key element for imaging the fetal brain in-utero using Magnetic Resonance Imaging (MRI). Maternal breathing can introduce motion, but a larger effect is frequently due to fetal movement within the womb. Consequently, imaging is frequently performed slice-by-slice using single shot techniques, which are then combined into volumetric images using slice-tovolume reconstruction methods (SVR). For successful SVR, a key preprocessing step is to isolate fetal brain tissues from maternal anatomy before correcting for the motion of the fetal head. This has hitherto been a manual or semi-automatic procedure. We propose an automatic method to localize and segment the brain of the fetus when the image data is acquired as stacks of 2D slices with anatomy misaligned due to fetal motion. We combine this segmentation process with a robust motion correction method, enabling the segmentation to be refined as the reconstruction proceeds. The fetal brain localization process uses Maximally Stable Extremal Regions (MSER), which are classified using a Bag-of-Words model with Scale-Invariant Feature Transform (SIFT) features. The segmentation process is a patch-based propagation of the MSER regions selected during detection, combined with a Conditional Random Field (CRF). The gestational age (GA) is used to incorporate prior knowledge about the size and volume of the fetal brain into the detection and segmentation process. The method was tested in a ten-fold cross-validation experiment on 66 datasets of healthy fetuses whose GA ranged from 22 to 39 weeks. In 85% of the tested cases, our proposed method produced a motion corrected volume of a relevant quality for clinical diagnosis, thus removing the need for manually delineating the contours of the brain before motion correction. Our method automatically generated as a side-product a segmentation of the reconstructed fetal brain with a mean Dice score of 93%, which can be used for further processing.

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“…Bach Cuedra et al [2] introduced separated Bayesian segmentation and Markov random field (MRF) regularization steps, the latter including anatomical priors. Other methods rely on motion-corrected 3D volumes, computed through reconstruction techniques of in utero MR scans [3,4]. Habas et al developed an automatic atlas-based segmentation [5], and a method including anatomical constraints in form of a laminar prior [6].…”

Section: Introductionmentioning

confidence: 99%

Segmentation of the cortex in fetal MRI using a topological model

Caldairou

Passat

Habas

et al. 2011

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

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The study of in utero fetal MR images is essential for the diagnosis of abnormal brain development and the study of the maturation of the brain structures. However, few automated segmentation methods have been developed so far, compare to the numerous ones existing for the adult brain anatomy, which is due to the particular properties of these images. In this paper, we propose a two-step cortex segmentation technique including anatomical priors and a topological model. Experiments performed on in utero MR data and validation by comparison to experts segmentation emphasize the relevance of the method.

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

Cited by 159 publications

References 26 publications

MRI of the foetal brain using a rapid 3D steady-state sequence

MRI of the foetal brain using a rapid 3D steady-state sequence

Automated fetal brain segmentation from 2D MRI slices for motion correction

Segmentation of the cortex in fetal MRI using a topological model

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