Adhesion-related small bowel obstruction: deep learning for automatic transition-zone detection by CT

Autor: Quentin Vanderbecq, Roberto Ardon, Antoine De Reviers, Camille Ruppli, Axel Dallongeville, Isabelle Boulay-Coletta, Gaspard D’Assignies, Marc Zins

Publikováno v: Insights into Imaging, Vol 13, Iss 1, Pp 1-9 (2022)

Abstract Background To train a machine-learning model to locate the transition zone (TZ) of adhesion-related small bowel obstruction (SBO) on CT scans. Materials and methods We used 562 CTs performed in 2005–2018 in 404 patients with adhesion-relat

Externí odkaz: https://doaj.org/article/0f5c167b955f4fb68b95ad1c6a6b6280

Re 'Pre-Surgical and Post-Surgical Aortic Aneurysm Maximum Diameter Measurement: Full Automation by Artificial Intelligence'

Autor: Chloé Adam, Roberto Ardon, Stéphan Haulon

Publikováno v: European Journal of Vascular and Endovascular Surgery. 63:525-526

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1fa407d92a7cb5714a15f005138789fa
https://doi.org/10.1016/j.ejvs.2021.11.001

Visual Explanation by Unifying Adversarial Generation and Feature Importance Attributions

Autor: Paul-Henry Cournède, Céline Hudelot, Roberto Ardon, Martin Charachon

Publikováno v: Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data ISBN: 9783030874438
iMIMIC/TDA4MedicalData@MICCAI

Explaining the decisions of deep learning models is critical for their adoption in medical practice. In this work, we propose to unify existing adversarial explanation methods and path-based feature importance attribution approaches. We consider a pa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ec5cc2bdce6dcaa19ed92e615145985f
https://doi.org/10.1007/978-3-030-87444-5_5

Pre-surgical and Post-surgical Aortic Aneurysm Maximum Diameter Measurement: Full Automation by Artificial Intelligence

Autor: Arshid Azarine, Justine Mougin, Stéphan Haulon, Dominique Fabre, Roberto Ardon, Marc Zins, Gaspard d’Assignies, Chloé Adam

Publikováno v: Journal of Vascular Surgery. 75:383

Objective The aim of this study was to evaluate an automatic, deep learning based method (Augmented Radiology for Vascular Aneurysm [ARVA]), to detect and assess maximum aortic diameter, providing cross sectional outer to outer aortic wall measuremen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15942ab12fbcbb1b61323225d508260b
https://doi.org/10.1016/j.jvs.2021.11.045

Multi-organ detection in 3D fetal ultrasound with machine learning

Autor: Laurence Rouet, Cybèle Ciofolo-Veit, Ibtisam Salim, Thierry Lefevre, Roberto Ardon, Caroline Raynaud, Aris T. Papageorghiou, A. Cavallaro

Publikováno v: Fetal, Infant and Ophthalmic Medical Image Analysis ISBN: 9783319675602
FIFI/OMIA@MICCAI

3D ultrasound (US) is a promising technique to perform automatic extraction of standard planes for fetal anatomy assessment. This requires prior organ localization, which is difficult to obtain with direct learning approaches because of the high vari

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10286470467c8234c6ed89ca59423e81
https://ora.ox.ac.uk/objects/uuid:af00a52b-bc29-43b4-a729-83de1fc11b8a