Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Bongjin Koo"'
Autor:
Thomas Dowrick, Guofang Xiao, Daniil Nikitichev, Eren Dursun, Niels van Berkel, Moustafa Allam, Bongjin Koo, Joao Ramalhinho, Stephen Thompson, Kurinchi Gurusamy, Ann Blandford, Danail Stoyanov, Brian R. Davidson, Matthew J. Clarkson
Publikováno v:
Dowrick, T, Xiao, G, Nikitichev, D, Dursun, E, van Berkel, N, Allam, M, Koo, B, Ramalhinho, J, Thompson, S, Gurusamy, K, Blandford, A, Stoyanov, D, Davidson, B R & Clarkson, M J 2023, ' Evaluation of a calibration rig for stereo laparoscopes ', Medical Physics, vol. 50, no. 5, pp. 2695-2704 . https://doi.org/10.1002/mp.16310
Background: Accurate camera and hand-eye calibration are essential to ensure high-quality results in image-guided surgery applications. The process must also be able to be undertaken by a nonexpert user in a surgical setting. Purpose: This work seeks
Publikováno v:
Computer Graphics Forum.
Designing realistic digital humans is extremely complex. Most data-driven generative models used to simplify the creation of their underlying geometric shape do not offer control over the generation of local shape attributes. In this paper, we overco
Autor:
João Ramalhinho, Bongjin Koo, Nina Montaña-Brown, Shaheer U. Saeed, Ester Bonmati, Kurinchi Gurusamy, Stephen P. Pereira, Brian Davidson, Yipeng Hu, Matthew J. Clarkson
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery. 17:1461-1468
Purpose The registration of Laparoscopic Ultrasound (LUS) to CT can enhance the safety of laparoscopic liver surgery by providing the surgeon with awareness on the relative positioning between critical vessels and a tumour. In an effort to provide a
Autor:
Thomas Dowrick, Stephen Thompson, Ester Bonmati, Goufang Xiao, Bongjin Koo, Mian Ahmad, Matthew J. Clarkson, Kim Kahl
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery
Purpose This paper introduces the SciKit-Surgery libraries, designed to enable rapid development of clinical applications for image-guided interventions. SciKit-Surgery implements a family of compact, orthogonal, libraries accompanied by robust testi
Autor:
Nina Montaña-Brown, João Ramalhinho, Bongjin Koo, Moustafa Allam, Brian Davidson, Kurinchi Gurusamy, Yipeng Hu, Matthew J. Clarkson
Publikováno v:
Simplifying Medical Ultrasound ISBN: 9783031169014
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::889a449e969658793356f83654e95e25
https://doi.org/10.1007/978-3-031-16902-1_18
https://doi.org/10.1007/978-3-031-16902-1_18
Publikováno v:
The Korean Journal of the Elementary Physical Education. 25:79-95
Autor:
Micha Pfeiffer, Brian R. Davidson, Kurinchi Selvan Gurusamy, Matthew J. Clarkson, Moustafa Allam, Bongjin Koo, Maria R. Robu, Stephen Thompson, David J Hawkes, Danail Stoyanov, Stefanie Speidel
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery
Purpose The initial registration of a 3D pre-operative CT model to a 2D laparoscopic video image in augmented reality systems for liver surgery needs to be fast, intuitive to perform and with minimal interruptions to the surgical intervention. Severa
Autor:
Simone Foti, Bongjin Koo, Danail Stoyanov, Matthew J. Clarkson, João Ramalhinho, Moustafa Allam, Brian R Davidson, Thomas Dowrick
Publikováno v:
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis ISBN: 9783030603649
UNSURE/GRAIL@MICCAI
UNSURE/GRAIL@MICCAI
In this work we propose a method based on geometric deep learning to predict the complete surface of the liver, given a partial point cloud of the organ obtained during the surgical laparoscopic procedure. We introduce a new data augmentation techniq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1d28f1efba4c7c38ad55c57a4c94472
https://doi.org/10.1007/978-3-030-60365-6_19
https://doi.org/10.1007/978-3-030-60365-6_19
Autor:
Matthew J. Clarkson, Bongjin Koo, Brian R Davidson, Crispin Schneider, Yipeng Hu, Yunguan Fu, Danail Stoyanov, Stijn van Laarhoven, Maria Robu
Publikováno v:
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data ISBN: 9783030333904
DART/MIL3ID@MICCAI
DART/MIL3ID@MICCAI
Improving a semi-supervised image segmentation task has the option of adding more unlabelled images, labelling the unlabelled images or combining both, as neither image acquisition nor expert labelling can be considered trivial in most clinical appli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd827bd75369f5cacdd3318a994920e1
https://doi.org/10.1007/978-3-030-33391-1_20
https://doi.org/10.1007/978-3-030-33391-1_20
Publikováno v:
Journal of Visceral Surgery
Journal of Visceral Surgery, Elsevier, 2019, 156, pp.261-262. ⟨10.1016/j.jviscsurg.2019.01.009⟩
Journal of Visceral Surgery, 2019, 156, pp.261-262. ⟨10.1016/j.jviscsurg.2019.01.009⟩
Journal of Visceral Surgery, Elsevier, 2019, 156, pp.261-262. ⟨10.1016/j.jviscsurg.2019.01.009⟩
Journal of Visceral Surgery, 2019, 156, pp.261-262. ⟨10.1016/j.jviscsurg.2019.01.009⟩