Segmentation of Intracranial Vessels and Aneurysms in Phase Contrast Magnetic Resonance Angiography Using Multirange Filters and Local Variances

Law, Max W. K.; Chung, Albert C. S.

doi:10.1109/tip.2012.2216274

Cited by 30 publications

(9 citation statements)

References 31 publications

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“…Based on the PCA venogram, semi-automated segmentation of major representative veins (superior sagittal sinus (SSS), straight sinus (StrS), transverse sinuses (TraS), and internal cerebral veins (ICVs)) was performed using ITK-SNAP's "active contour segmentation mode" (Bettoni et al, 2018;Law and Chung, 2012). Here, the TraS segment comprised the transverse sinuses, extending into the sigmoid sinuses and the internal jugular veins.…”

Section: Single-vein Segmentationmentioning

confidence: 99%

Investigating the Effect of Flow Compensation and Quantitative Susceptibility Mapping Method on the Accuracy of Venous Susceptibility Measurement

Berg

Preibisch

Thomas³

et al. 2021

Preprint

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Quantitative susceptibility mapping (QSM) is a promising non-invasive method for obtaining information relating to the oxygen metabolism. However, the optimal acquisition sequence and QSM reconstruction method for reliable venous susceptibility measurements are unknown. Full flow compensation is generally recommended to correct for the influence of venous blood flow, although the effect of flow compensation on the accuracy of venous susceptibility values has not been systematically evaluated. In this study, we investigated the effect of different acquisition sequences, including different flow compensation schemes, and different QSM reconstruction methods on venous susceptibilities. Ten healthy subjects were scanned with five or six distinct QSM sequence designs implementing different flow compensation schemes. All data sets were processed using six different QSM pipelines and venous blood susceptibility was evaluated in whole-brain segmentations of the venous vasculature and single veins. The quality of vein segmentations and the accuracy of venous susceptibility values were analyzed and compared between all combinations of sequences and QSM methods. The influence of the QSM method on average venous susceptibility values was found to be 2.7 - 11.6 times greater than the influence of the acquisition sequence, including flow compensation. The majority of the investigated QSM reconstruction methods tended to underestimate venous susceptibility values in the vein segmentations that were obtained. Using multi-echo gradient-echo acquisitions with monopolar readout gradients, we found that sequences without full flow compensation yielded venous susceptibility values comparable to sequences with full flow compensation. However, the QSM method had a great influence on susceptibility values and thus needs to be considered carefully for accurate venous QSM.

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Section: Single-vein Segmentationmentioning

confidence: 99%

Investigating the Effect of Flow Compensation and Quantitative Susceptibility Mapping Method on the Accuracy of Venous Susceptibility Measurement

Berg

Preibisch

Thomas³

et al. 2021

Preprint

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“…Therefore, there is a need to enhance these images in order to obtain a good segmentation of the LC beams. Enhancement of curvilinear structures for the purpose of detection or segmentation has been proposed in a number of clinical applications, such as for extracting individual filaments in confocal and total internal reflectance fluorescence (TIRF) microscopy images [41], blood vessel extraction in retinal fundus images [42]–[44], segmentation of intracranial vessels in phase-contrast magnetic resonance angiographic (PC-MRA) images [45], detection and tracking of vehicles in wide area aerial images [46], and neuron detection and segmentation in microscopy images [47]–[49]. In this work, we use the isotropic undecimated wavelet transform (IUWT), which has been used for astronomical [50] and biological [51] applications.…”

Section: Methodsmentioning

confidence: 99%

Three-Dimensional Segmentation of the <italic>Ex-Vivo</italic> Anterior Lamina Cribrosa From Second-Harmonic Imaging Microscopy

Ram

Danford

Howerton

et al. 2018

IEEE Trans. Biomed. Eng.

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The lamina cribrosa (LC) is a connective tissue in the posterior eye with a complex mesh-like trabecular microstructure through which all the retinal ganglion cell axons and central retinal vessels pass. Recent studies have demonstrated that changes in the structure of the LC correlate with glaucomatous damage. Thus, accurate segmentation and reconstruction of the LC is of utmost importance. This paper presents a new automated method for segmenting the microstructure of the anterior LC in the images obtained via multiphoton microscopy using a combination of ideas. In order to reduce noise, we first smooth the input image using a 4-D collaborative filtering scheme. Next, we enhance the beam-like trabecular microstructure of the LC using wavelet multiresolution analysis. The enhanced LC microstructure is then automatically extracted using a combination of histogram thresholding and graph-cuts binarization. Finally, we use morphological area opening as a post-processing step to remove the small and unconnected 3-D regions in the binarized images. The performance of the proposed method is evaluated using mutual overlap accuracy, Tanimoto index, F-score, and Rand index. Quantitative and qualitative results show that the proposed algorithm provides improved segmentation accuracy and computational efficiency compared to the other recent algorithms.

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“…The results prove that this method is highly sensitive and can potentially assist treating physicians in aSAH by providing automated detection and segmentation of aneurysms. Law et al [ 33 ] proposed a novel intensity-based algorithm to segment intracranial vessels and the attached aneurysms, which can handle the low-contrast aneurysmal regions affected by turbulent flows. It is grounded on multirange filters and local variances to extract intensity-based image features.…”

Section: Related Workmentioning

confidence: 99%

OTO-Net: An Automated MRA Image Segmentation Network for Intracranial Aneurysms

et al. 2022

Computational Intelligence and Neuroscience

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Intracranial aneurysms are local dilations of the cerebral blood vessels; people with intracranial aneurysms have a high risk to cause bleeding in the brain, which is related to high mortality and morbidity rates. Accurate detection and segmentation of intracranial aneurysms from Magnetic Resonance Angiography (MRA) images are essential in the clinical routine. Manual annotations used to assess the intracranial aneurysms on MRA images are substantial interobserver variability for both aneurysm detection and assessment of aneurysm size and growth. Many prior automated segmentation works have focused their efforts on tackling the problem, but there is still room for performance improvement due to the significant variability of lesions in the location, size, structure, and morphological appearance. To address these challenges, we propose a novel One-Two-One Fully Convolutional Networks (OTO-Net) for intracranial aneurysms automated segmentation in MRA images. The OTO-Net uses full convolution to achieve intracranial aneurysms automated segmentation through the combination of downsampling, upsampling, and skip connection. In addition, loss ensemble is used as the objective function to steadily improve the backpropagation efficiency of the network structure during the training process. We evaluated the proposed OTO-Net on one public benchmark dataset and one private dataset. Our proposed model can achieve the automated segmentation accuracy with 98.37% and 97.86%, average surface distances with 1.081 and 0.753, dice similarity coefficients with 0.9721 and 0.9813, and Hausdorff distance with 0.578 and 0.642 on these two datasets, respectively.

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Segmentation of Intracranial Vessels and Aneurysms in Phase Contrast Magnetic Resonance Angiography Using Multirange Filters and Local Variances

Cited by 30 publications

References 31 publications

Investigating the Effect of Flow Compensation and Quantitative Susceptibility Mapping Method on the Accuracy of Venous Susceptibility Measurement

Investigating the Effect of Flow Compensation and Quantitative Susceptibility Mapping Method on the Accuracy of Venous Susceptibility Measurement

Three-Dimensional Segmentation of the <italic>Ex-Vivo</italic> Anterior Lamina Cribrosa From Second-Harmonic Imaging Microscopy

OTO-Net: An Automated MRA Image Segmentation Network for Intracranial Aneurysms

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