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Automatic Segmentation of Neonatal Ventricles from Cranial Ultrasound for Prediction of Intraventricular Hemorrhage Outcome.

P. Tabrizi, R. Obeid, J. Cerrolaza, A. Penn, A. Mansoor, and M. Linguraru. EMBC, page 3136-3139. IEEE, (2018)

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Correction to Ä Generic Approach to Pathological Lung Segmentation".A. Mansoor, U. Bagci, Z. Xu, B. Foster, K. Olivier, J. Elinoff, A. Suffredini, J. Udupa, and D. Mollura. IEEE Trans. Med. Imaging, 34 (1): 354 (2015)A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT.Z. Xu, U. Bagci, B. Foster, A. Mansoor, J. Udupa, and D. Mollura. Medical Image Analysis, 24 (1): 1-17 (2015)Spatially Constrained Random Walk Approach for Accurate Estimation of Airway Wall Surfaces.Z. Xu, U. Bagci, B. Foster, A. Mansoor, and D. Mollura. MICCAI (2), volume 8150 of Lecture Notes in Computer Science, page 559-566. Springer, (2013)BiofilmQuant: A computer-assisted tool for dental biofilm quantification.A. Mansoor, V. Patsekin, D. Scherl, J. Robinson, and B. Rajwa. EMBC, page 4244-4247. IEEE, (2014)Marginal shape deep learning: applications to pediatric lung field segmentation.A. Mansoor, J. Cerrolaza, G. Perez, E. Biggs, G. Nino, and M. Linguraru. Medical Imaging: Image Processing, volume 10133 of SPIE Proceedings, page 1013304. SPIE, (2017)Cranial ultrasound-based prediction of post hemorrhagic hydrocephalus outcome in premature neonates with intraventricular hemorrhage.P. Tabrizi, R. Obeid, A. Mansoor, S. Ensel, J. Cerrolaza, A. Penn, and M. Linguraru. EMBC, page 169-172. IEEE, (2017)Identification of dysmorphic syndromes using landmark-specific local texture descriptors.J. Cerrolaza, A. Porras, A. Mansoor, Q. Zhao, M. Summar, and M. Linguraru. ISBI, page 1080-1083. IEEE, (2016)Region Proposal Networks with Contextual Selective Attention for Real-Time Organ Detection.A. Mansoor, A. Porras, and M. Linguraru. CoRR, (2018)A Statistical Modeling Approach to Computer-Aided Quantification of Dental Biofilm.A. Mansoor, V. Patsekin, D. Scherl, J. Robinson, and B. Rajwa. CoRR, (2014)Deep Learning Guided Partitioned Shape Model for Anterior Visual Pathway Segmentation.A. Mansoor, J. Cerrolaza, R. Idrees, E. Biggs, M. Alsharid, R. Avery, and M. Linguraru. IEEE Trans. Med. Imaging, 35 (8): 1856-1865 (2016)

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Automatic Segmentation of Neonatal Ventricles from Cranial Ultrasound for Prediction of Intraventricular Hemorrhage Outcome.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Automatic Segmentation of Neonatal Ventricles from Cranial Ultrasound for Prediction of Intraventricular Hemorrhage Outcome.

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Automatic Segmentation of Neonatal Ventricles from Cranial Ultrasound for Prediction of Intraventricular Hemorrhage Outcome.