Search Results for author: Io Flament

Found 2 papers, 1 papers with code

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

2 code implementations • 29 Apr 2020 • Arjun D. Desai, Francesco Caliva, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew Torigian, Jutta Ellermann, Mehmet Akcakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O`Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry E. Gold, Brian A. Hargreaves, Valentina Pedoia, Akshay S. Chaudhari

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression.

MRI segmentation Segmentation

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Hierarchical Severity Staging of Anterior Cruciate Ligament Injuries using Deep Learning with MRI Images

no code implementations • 20 Mar 2020 • Nikan K. Namiri, Io Flament, Bruno Astuto, Rutwik Shah, Radhika Tibrewala, Francesco Caliva, Thomas M. Link, Valentina Pedoia, Sharmila Majumdar

Results: The overall accuracy and weighted Cohen's kappa reported for ACL injury classification were higher using the 2D CNN (accuracy: 92% (233/254) and kappa: 0. 83) than the 3D CNN (accuracy: 89% (225/254) and kappa: 0. 83) (P = . 27).

General Classification Lesion Classification +1

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