J
Jaime Melendez
Researcher at Radboud University Nijmegen
Publications - 33
Citations - 1169
Jaime Melendez is an academic researcher from Radboud University Nijmegen. The author has contributed to research in topics: Contextual image classification & Texture filtering. The author has an hindex of 18, co-authored 32 publications receiving 855 citations. Previous affiliations of Jaime Melendez include Analysis Group & Rovira i Virgili University.
Papers
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Journal ArticleDOI
COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System.
Keelin Murphy,Henk Smits,Arnoud J. G. Knoops,Michael B. J. M. Korst,Tijs Samson,Ernst T. Scholten,Steven Schalekamp,Cornelia M. Schaefer-Prokop,Rick H. H. M. Philipsen,Annet Meijers,Jaime Melendez,Bram van Ginneken,Matthieu Rutten +12 more
TL;DR: The performance of an artificial intelligence system in the detection of coronavirus disease 2019 on chest radiographs was comparable with that of six independent readers at their highest possible sensitivities.
Journal ArticleDOI
Automated localization of breast cancer in DCE-MRI
Albert Gubern-Mérida,Albert Gubern-Mérida,Robert Martí,Jaime Melendez,Jakob L. Hauth,Ritse M. Mann,Nico Karssemeijer,Bram Platel +7 more
TL;DR: A novel automated breast cancer localization system for DCE-MRI that initially corrects for motion artifacts and segments the breast, and a malignancy score for each lesion candidate is obtained using region-based morphological and kinetic features computed on the segmented lesion candidates.
Journal ArticleDOI
A Novel Multiple-Instance Learning-Based Approach to Computer-Aided Detection of Tuberculosis on Chest X-Rays
Jaime Melendez,Bram van Ginneken,Pragnya Maduskar,Rick H. H. M. Philipsen,Klaus Reither,Marianne Breuninger,Ifedayo M. O. Adetifa,Rahmatulai Maane,Helen Ayles,Clara I. Sánchez +9 more
TL;DR: This paper proposes an improved algorithm that overcomes miSVM's drawbacks related to positive instance underestimation and costly iteration, namely multiple-instance learning (MIL), that does not require detailed information for optimization.
Journal ArticleDOI
An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information.
Jaime Melendez,Clara I. Sánchez,Rick H. H. M. Philipsen,Pragnya Maduskar,Rodney Dawson,Grant Theron,Grant Theron,Keertan Dheda,Bram van Ginneken +8 more
TL;DR: This framework is evaluated on a database containing 392 patient records from suspected TB subjects prospectively recruited in Cape Town, South Africa and indicates that combining CAD and clinical information to estimate the risk of active disease is a promising tool for TB screening.
Journal ArticleDOI
Breast tumor classification in ultrasound images using texture analysis and super-resolution methods
TL;DR: It is shown that the super-resolution-based approach improves the performance of the evaluated texture methods and thus outperforms the state of the art in benign/malignant tumor classification.