Neeraja Konuthula1, Francisco A Perez2,3, A Murat Maga4,5, Waleed M Abuzeid1, Kris Moe1,6, Blake Hannaford7, Randall A Bly8,9. 1. Department of Otolaryngology, Head and Neck Surgery, University of Washington, Seattle, WA, USA. 2. Department of Radiology, University of Washington, Seattle, WA, USA. 3. Division of Radiology, Seattle Children's Hospital, Seattle, WA, USA. 4. Department of Craniofacial Medicine, University of Washington, Seattle, WA, USA. 5. Craniofacial Center, Seattle Children's Hospital, Seattle, WA, USA. 6. Otolaryngology-Head and Neck Surgery, Harborview Medical Center, Seattle, WA, USA. 7. Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA. 8. Department of Otolaryngology, Head and Neck Surgery, University of Washington, Seattle, WA, USA. randbly@uw.edu. 9. Division of Pediatric Otolaryngology, Head and Neck Surgery, Seattle Children's Hospital, Seattle, WA, USA. randbly@uw.edu.
Abstract
PURPOSE: Computational surgical planning tools could help develop novel skull base surgical approaches that improve safety and patient outcomes. This defines a need for automated skull base segmentation to improve the usability of surgical planning software. The objective of this work was to design and validate an algorithm for atlas-based automated segmentation of skull base structures in individual image sets for skull base surgical planning. METHODS: Advanced Normalization Tools software was used to construct a synthetic CT template from 6 subjects, and skull base structures were manually segmented to create a reference atlas. Landmark registration followed by Elastix deformable registration was applied to the template to register it to each of the 30 trusted reference image sets. Dice coefficient, average Hausdorff distance, and clinical usability scoring were used to compare the atlas segmentations to those of the trusted reference image sets. RESULTS: The mean for average Hausdorff distance for all structures was less than 2 mm (mean for 95th percentile Hausdorff distance was less than 5 mm). For structures greater than 2.5 mL in volume, the average Dice coefficient was 0.73 (range 0.59-0.82), and for structures less than 2.5 mL in volume the Dice coefficient was less than 0.7. The usability scoring survey was completed by three experts, and all structures met the criteria for acceptable effort except for the foramen spinosum, rotundum, and carotid artery, which required more than minor corrections. CONCLUSION: Currently available open-source algorithms, such as the Elastix deformable algorithm, can be used for automated atlas-based segmentation of skull base structures with acceptable clinical accuracy and minimal corrections with the use of the proposed atlas. The first publicly available CT template and anterior skull base segmentation atlas being released (available at this link: http://hdl.handle.net/1773/46259 ) with this paper will allow for general use of automated atlas-based segmentation of the skull base.
PURPOSE: Computational surgical planning tools could help develop novel skull base surgical approaches that improve safety and patient outcomes. This defines a need for automated skull base segmentation to improve the usability of surgical planning software. The objective of this work was to design and validate an algorithm for atlas-based automated segmentation of skull base structures in individual image sets for skull base surgical planning. METHODS: Advanced Normalization Tools software was used to construct a synthetic CT template from 6 subjects, and skull base structures were manually segmented to create a reference atlas. Landmark registration followed by Elastix deformable registration was applied to the template to register it to each of the 30 trusted reference image sets. Dice coefficient, average Hausdorff distance, and clinical usability scoring were used to compare the atlas segmentations to those of the trusted reference image sets. RESULTS: The mean for average Hausdorff distance for all structures was less than 2 mm (mean for 95th percentile Hausdorff distance was less than 5 mm). For structures greater than 2.5 mL in volume, the average Dice coefficient was 0.73 (range 0.59-0.82), and for structures less than 2.5 mL in volume the Dice coefficient was less than 0.7. The usability scoring survey was completed by three experts, and all structures met the criteria for acceptable effort except for the foramen spinosum, rotundum, and carotid artery, which required more than minor corrections. CONCLUSION: Currently available open-source algorithms, such as the Elastix deformable algorithm, can be used for automated atlas-based segmentation of skull base structures with acceptable clinical accuracy and minimal corrections with the use of the proposed atlas. The first publicly available CT template and anterior skull base segmentation atlas being released (available at this link: http://hdl.handle.net/1773/46259 ) with this paper will allow for general use of automated atlas-based segmentation of the skull base.
Authors: T Schiemann; J Freudenberg; B Pflesser; A Pommert; K Priesmeyer; M Riemer; R Schubert; U Tiede; K H Höhne Journal: Comput Med Imaging Graph Date: 2000 May-Jun Impact factor: 4.790
Authors: Keelin Murphy; Bram van Ginneken; Joseph M Reinhardt; Sven Kabus; Kai Ding; Xiang Deng; Kunlin Cao; Kaifang Du; Gary E Christensen; Vincent Garcia; Tom Vercauteren; Nicholas Ayache; Olivier Commowick; Grégoire Malandain; Ben Glocker; Nikos Paragios; Nassir Navab; Vladlena Gorbunova; Jon Sporring; Marleen de Bruijne; Xiao Han; Mattias P Heinrich; Julia A Schnabel; Mark Jenkinson; Cristian Lorenz; Marc Modat; Jamie R McClelland; Sébastien Ourselin; Sascha E A Muenzing; Max A Viergever; Dante De Nigris; D Louis Collins; Tal Arbel; Marta Peroni; Rui Li; Gregory C Sharp; Alexander Schmidt-Richberg; Jan Ehrhardt; René Werner; Dirk Smeets; Dirk Loeckx; Gang Song; Nicholas Tustison; Brian Avants; James C Gee; Marius Staring; Stefan Klein; Berend C Stoel; Martin Urschler; Manuel Werlberger; Jef Vandemeulebroucke; Simon Rit; David Sarrut; Josien P W Pluim Journal: IEEE Trans Med Imaging Date: 2011-05-31 Impact factor: 10.048
Authors: Patrik F Raudaschl; Paolo Zaffino; Gregory C Sharp; Maria Francesca Spadea; Antong Chen; Benoit M Dawant; Thomas Albrecht; Tobias Gass; Christoph Langguth; Marcel Lüthi; Florian Jung; Oliver Knapp; Stefan Wesarg; Richard Mannion-Haworth; Mike Bowes; Annaliese Ashman; Gwenael Guillard; Alan Brett; Graham Vincent; Mauricio Orbes-Arteaga; David Cárdenas-Peña; German Castellanos-Dominguez; Nava Aghdasi; Yangming Li; Angelique Berens; Kris Moe; Blake Hannaford; Rainer Schubert; Karl D Fritscher Journal: Med Phys Date: 2017-04-21 Impact factor: 4.071
Authors: David Steybe; Philipp Poxleitner; Marc Christian Metzger; Leonard Simon Brandenburg; Rainer Schmelzeisen; Fabian Bamberg; Phuong Hien Tran; Elias Kellner; Marco Reisert; Maximilian Frederik Russe Journal: Int J Comput Assist Radiol Surg Date: 2022-06-03 Impact factor: 3.421