Interactive exploration of a 3D intracranial aneurysm wall model extracted from histologic slices
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Bernhard Preim | Sylvia Saalfeld | Martin Skalej | Simon Weigand | Annika Niemann | Thomas Hoffmann | Riikka Tulamo | M. Skalej | B. Preim | S. Saalfeld | T. Hoffmann | R. Tulamo | Annika Niemann | S. Weigand
[1] Petri Honkanen,et al. Loss of Mural Cells Leads to Wall Degeneration, Aneurysm Growth, and Eventual Rupture in a Rat Aneurysm Model , 2014, Stroke.
[2] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[3] M. Taneda,et al. Structural fragility and inflammatory response of ruptured cerebral aneurysms. A comparative study between ruptured and unruptured cerebral aneurysms. , 1999, Stroke.
[4] Yi Qian,et al. Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)—phase II: rupture risk assessment , 2019, International Journal of Computer Assisted Radiology and Surgery.
[5] Bernhard Preim,et al. Fluid-Structure Simulations of a Ruptured Intracranial Aneurysm: Constant versus Patient-Specific Wall Thickness , 2016, Comput. Math. Methods Medicine.
[6] M. Mallar Chakravarty,et al. The creation of a brain atlas for image guided neurosurgery using serial histological data , 2006, NeuroImage.
[7] D. Stuss,et al. Effects of lateral lesions on medial activation during autobiographical remembering , 2010 .
[8] Gábor Székely,et al. A mean three-dimensional atlas of the human thalamus: Generation from multiple histological data , 2009 .
[9] N. Otsu. A threshold selection method from gray level histograms , 1979 .
[10] A. Annadhason. Medical Image Analysis , 2011 .
[11] Nasir M. Rajpoot,et al. Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images , 2016, IEEE Trans. Medical Imaging.
[12] S. Juvela,et al. Natural history of unruptured intracranial aneurysms: probability of and risk factors for aneurysm rupture. , 2008, Journal of neurosurgery.
[13] Marc Lartaud,et al. Analyzing huge pathology images with open source software , 2013, Diagnostic Pathology.
[14] Sylvia Saalfeld,et al. Suitability of intravascular imaging for assessment of cerebrovascular diseases , 2019, Neuroradiology.
[15] Alejandro F. Frangi,et al. Biomechanical wall properties of human intracranial aneurysms resected following surgical clipping , 2011 .
[16] Alejandro F. Frangi,et al. Reproducibility of image-based computational hemodynamics in intracranial aneurysms: Comparison of CTA AND 3DRA , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[17] M. Miller,et al. Large Deformation Diffeomorphic Metric Mapping Registration of Reconstructed 3D Histological Section Images and in vivo MR Images , 2009, Front. Hum. Neurosci..
[18] Bernhard Preim,et al. Virtual Inflation of the Cerebral Artery Wall for the Integrated Exploration of OCT and Histology Data , 2017, Comput. Graph. Forum.
[19] Juha Hernesniemi,et al. Inflammatory changes in the aneurysm wall: a review , 2018, Journal of NeuroInterventional Surgery.
[20] Marko Kangasniemi,et al. Remodeling of Saccular Cerebral Artery Aneurysm Wall Is Associated With Rupture: Histological Analysis of 24 Unruptured and 42 Ruptured Cases , 2004, Stroke.
[21] Juan R. Cebral,et al. Diversity in the Strength and Structure of Unruptured Cerebral Aneurysms , 2015, Annals of Biomedical Engineering.
[22] M. L. Raghavan,et al. Quantified aneurysm shape and rupture risk. , 2005, Journal of neurosurgery.
[23] Adel Hafiane,et al. Fuzzy Clustering and Active Contours for Histopathology Image Segmentation and Nuclei Detection , 2008, ACIVS.
[24] Hao Chen,et al. DCAN: Deep contour‐aware networks for object instance segmentation from histology images , 2017, Medical Image Anal..