S
Sabine Sarnacki
Researcher at Necker-Enfants Malades Hospital
Publications - 214
Citations - 6682
Sabine Sarnacki is an academic researcher from Necker-Enfants Malades Hospital. The author has contributed to research in topics: Medicine & Transplantation. The author has an hindex of 38, co-authored 188 publications receiving 5599 citations. Previous affiliations of Sabine Sarnacki include French Institute of Health and Medical Research & Paris Descartes University.
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Journal ArticleDOI
La transplantation intestinale
Olivier Goulet,Dominique Jan,Nicole Brousse,Danielle Canioni,Sabine Sarnacki,Claude Ricour,Yann Revillon +6 more
TL;DR: Les resultats actuels de the transplantation intestinale, nettement ameliores depuis l'utilisation du FK-506, justifient d'envisager plus largement cette therapeutique - rend compte de cette situation.
Journal ArticleDOI
Outcome of Total Colonic Aganglionosis Involving the Small Bowel Depends on Bowel Length, Liver Disease, and Enterocolitis
E. Payen,Cécile Talbotec,Christophe Chardot,Carmen Capito,Naziha Khen-Dunlop,Sabine Sarnacki,Florence Lacaille,Cécile Lambe,Olivier Goulet +8 more
TL;DR:
Towards building 3D individual models from MRI segmentation and tractography to enhance surgical planning for pediatric pelvic tumors and malformations
Cécile Muller,Alessio Virzi,Jean-Baptiste Marret,Eva Mille,Laureline Berteloot,David Grevent,Thomas Blanc,Nicolas Garcelon,Isabelle Buffet,Elisabeth Hullier-Ammard,Pietro Gori,Nathalie Boddaert,Isabelle Bloch,Sabine Sarnacki +13 more
Proceedings ArticleDOI
Automatic Size And Pose Homogenization With Spatial Transformer Network To Improve And Accelerate Pediatric Segmentation
Giammarco La Barbera,Pietro Gori,Haithem Boussaid,Bruno Belucci,Alessandro Delmonte,Jeanne Goulin,Sabine Sarnacki,Laurence Rouet,Isabelle Bloch +8 more
TL;DR: In this article, the authors proposed a new CNN architecture that is pose and scale invariant thanks to the use of Spatial Transformer Network (STN), which is composed of three sequential modules that are estimated together during training: a regression module to estimate a similarity matrix to normalize the input image to a reference one, a differentiable module to find the region of interest to segment, and a segmentation module, based on the popular UNet architecture, to delineate the object.
Journal ArticleDOI
Robotic Surgery in Pediatric Oncology: Lessons Learned from the First 100 Tumours. A Nationwide Experience
Thierry Blanc,P. Meignan,Nicolas Vinit,Quentin Ballouhey,Luca Pio,Carmen Capito,Caroline Harte,Fabrizio Vatta,Louise Galmiche-Rolland,Véronique Minard,Daniel Orbach,Laureline Berteloot,Cécile Muller,Jules Kohaut,A Broch,Karim Braik,Aurélien Binet,Yves Heloury,Laurent Fourcade,Hubert Lardy,Sabine Sarnacki +20 more
TL;DR: Robotic surgery for paediatric tumours is feasible and may be an option in highly selected cases and should be discussed by tumour boards to avoid widespread and uncontrolled application of the approach.