J
Jan-Jurre Mordang
Researcher at Radboud University Nijmegen
Publications - 19
Citations - 583
Jan-Jurre Mordang is an academic researcher from Radboud University Nijmegen. The author has contributed to research in topics: Mammography & Microcalcification. The author has an hindex of 8, co-authored 19 publications receiving 359 citations. Previous affiliations of Jan-Jurre Mordang include Radboud University Nijmegen Medical Centre.
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Journal ArticleDOI
Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System
Alejandro Rodriguez-Ruiz,Elizabeth A. Krupinski,Jan-Jurre Mordang,Kathy Schilling,Sylvia H. Heywang-Köbrunner,Ioannis Sechopoulos,Ritse M. Mann +6 more
TL;DR: Radiologists improved their cancer detection at mammography when using an artificial intelligence system for support, without requiring additional reading time.
Book ChapterDOI
Automatic Microcalcification Detection in Multi-vendor Mammography Using Convolutional Neural Networks
Jan-Jurre Mordang,Tim Janssen,Alessandro Bria,Thijs Kooi,Albert Gubern-Mérida,Nico Karssemeijer +5 more
TL;DR: This was the first study to use a deep learning strategy for the detection of microcalcifications in mammograms, and significantly higher mean sensitivities were obtained with the CNN on the mammograms of each individual manufacturer compared to the cascade classifier.
Book ChapterDOI
A Comparison Between a Deep Convolutional Neural Network and Radiologists for Classifying Regions of Interest in Mammography
Thijs Kooi,Albert Gubern-Mérida,Jan-Jurre Mordang,Ritse M. Mann,Ruud M. Pijnappel,Klaas H. Schuur,Ard den Heeten,Nico Karssemeijer +7 more
TL;DR: A deep Convolutional Neural Network CNN is employed for the classification of regions of interest of malignant soft tissue lesions in mammography and it is shown that it performs on par to experienced radiologists.
Journal ArticleDOI
Computer-aided detection of breast cancers using Haar-like features in automated 3D breast ultrasound.
Tao Tan,Jan-Jurre Mordang,Jan van Zelst,André Grivegnée,Albert Gubern-Mérida,Jaime Melendez,Ritse M. Mann,Wei Zhang,Bram Platel,Nico Karssemeijer +9 more
TL;DR: This work significantly improves the previously developed CADe system in the initial candidate detection stage of automated 3D breast ultrasound by using a large number of 2D Haar-like features to differentiate lesion structures from false positives.
Journal ArticleDOI
The importance of early detection of calcifications associated with breast cancer in screening
Jan-Jurre Mordang,Albert Gubern-Mérida,Alessandro Bria,Francesco Tortorella,Ritse M. Mann,Mireille J. M. Broeders,G. J Den Heeten,Nico Karssemeijer +7 more
TL;DR: Screening sensitivity for detection of malignant calcifications is low, and the majority of lesions with detectable calcifications that are not recalled immediately but detected as interval cancer or in the next screening round are invasive at the time of diagnosis.