A surface registration approach for video-based analysis of intraoperative brain surface deformations.

Anatomical intra operative deformation is a major limitation of accuracy in image guided neurosurgery. Approaches to quantify these deforamations based on 3D reconstruction of surfaces have been introduced. For accurate quantification of surface deformation, a robust surface registration method is required. In this paper, we propose a new surface registration for video-based analysis of intraoperative brain deformations. This registration method includes three terms: the first term is related to image intensities, the second to Euclidean distance and the third to anatomical landmarks continuously tracked in 2D video. This new surface registration method can be used with any cortical surface textured point cloud computed by stereoscopic or laser range approaches. We have shown the global method, including textured point cloud reconstruction, had a precision within 2 millimeters, which is within the usual rigid registration error of the neuronavigation system before deformations

A surface registration approach for video-based analysis of intraoperative brain surface deformations.

Anatomical intra operative deformation is a major limitation of accuracy in image guided neurosurgery. Approaches to quantify these deforamations based on 3D reconstruction of surfaces have been introduced. For accurate quantification of surface deformation, a robust surface registration method is required. In this paper, we propose a new surface registration for video-based analysis of intraoperative brain deformations. This registration method includes three terms: the first term is related to image intensities, the second to Euclidean distance and the third to anatomical landmarks continuously tracked in 2D video. This new surface registration method can be used with any cortical surface textured point cloud computed by stereoscopic or laser range approaches. We have shown the global method, including textured point cloud reconstruction, had a precision within 2 millimeters, which is within the usual rigid registration error of the neuronavigation system before deformations

A surface registration approach for video-based analysis of intraoperative brain surface deformations.

Anatomical intra operative deformation is a major limitation of accuracy in image guided neurosurgery. Approaches to quantify these deforamations based on 3D reconstruction of surfaces have been introduced. For accurate quantification of surface deformation, a robust surface registration method is required. In this paper, we propose a new surface registration for video-based analysis of intraoperative brain deformations. This registration method includes three terms: the first term is related to image intensities, the second to Euclidean distance and the third to anatomical landmarks continuously tracked in 2D video. This new surface registration method can be used with any cortical surface textured point cloud computed by stereoscopic or laser range approaches. We have shown the global method, including textured point cloud reconstruction, had a precision within 2 millimeters, which is within the usual rigid registration error of the neuronavigation system before deformations

A surface registration approach for video-based analysis of intraoperative brain surface deformations

Anatomical intra operative deformation is a major limitation of accuracy in image guided neurosurgery. Approaches to quantify these deforamations based on 3D reconstruction of surfaces have been introduced. For accurate quantification of surface deformation, a robust surface registration method is required. In this paper, we propose a new surface registration for video-based analysis of intraoperative brain deformations. This registration method includes three terms: the first term is related to image intensities, the second to Euclidean distance and the third to anatomical landmarks continuously tracked in 2D video. This new surface registration method can be used with any cortical surface textured point cloud computed by stereoscopic or laser range approaches. We have shown the global method, including textured point cloud reconstruction, had a precision within 2 millimeters, which is within the usual rigid registration error of the neuronavigation system before deformations

A surface registration approach for video-based analysis of intraoperative brain surface deformations.

Anatomical intra operative deformation is a major limitation of accuracy in image guided neurosurgery. Approaches to quantify these deforamations based on 3D reconstruction of surfaces have been introduced. For accurate quantification of surface deformation, a robust surface registration method is required. In this paper, we propose a new surface registration for video-based analysis of intraoperative brain deformations. This registration method includes three terms: the first term is related to image intensities, the second to Euclidean distance and the third to anatomical landmarks continuously tracked in 2D video. This new surface registration method can be used with any cortical surface textured point cloud computed by stereoscopic or laser range approaches. We have shown the global method, including textured point cloud reconstruction, had a precision within 2 millimeters, which is within the usual rigid registration error of the neuronavigation system before deformations

Ureteropelvic junction obstruction with primary lymphoedema associated with<i>CELSR1</i>variants

Background Primary lymphoedema (PL) is a chronic, debilitating disease caused by developmental and functional defects of the lymphatic system. It is marked by an accumulation of interstitial fluid, fat and tissue fibrosis. There is no cure. More than 50 genes and genetic loci have been linked to PL. We sought to study systematically cell polarity signalling protein Cadherin Epidermal Growth Factor Laminin G Seven-pass G-type Receptor 1 (CELSR1) variants linked to PL. Methods We investigated 742 index patients from our PL cohort using exome sequencing. Results We identified nine variants predicted to cause CELSR1 loss of function. Four of them were tested for nonsense-mediated mRNA decay, but none was observed. Most of the truncated CELSR1 proteins would lack the transmembrane domain, if produced. The affected individuals had puberty/late-onset PL on lower extremities. The variants had a statistically significant difference in penetrance between female patients (87%) and male patients (20%). Eight variant carriers had a kidney anomaly, mostly in the form of ureteropelvic junction obstruction, which has not been associated with CELSR1 before. CELSR1 is located in the 22q13.3 deletion locus of the Phelan-McDermid syndrome. As variable renal defects are often seen in patients with the Phelan-McDermid syndrome, CELSR1 may be the long-sought gene for the renal defects. Conclusion PL associated with a renal anomaly suggests a CELSR1-related cause