Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Automated linking of suspicious findings between automated 3D breast ultrasound volumes.

A. Gubern-Mérida, T. Tan, J. van Zelst, R. Mann, and N. Karssemeijer. Medical Imaging: Computer-Aided Diagnosis, volume 9785 of SPIE Proceedings, page 97850N. SPIE, (2016)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Univ. -Prof. Dr. Albert Jeltsch University of Stuttgart

Dr. Albert Julius Rostas University of Stuttgart

Hon. -Prof. Dr. Albert Nonnenmacher University of Stuttgart

Albert Emrich University of Stuttgart

apl. Prof. Dr. -Ing. Albert Bursik University of Stuttgart

Other publications of authors with the same name

Changes in breast density over time using automatic density measures: preliminary analysis.E. García, A. Oliver, O. Díaz, Y. Diez, A. Gubern-Mérida, J. Martí, and R. Martí. IWBI, volume 10718 of SPIE Proceedings, page 107181I. SPIE, (2018)Comparison of Methods for Current-to-Prior Registration of Breast DCE-MRI.Y. Diez, A. Gubern-Mérida, L. Wang, S. Diekmann, J. Martí, B. Platel, J. Kramme, and R. Marti. Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 689-695. Springer, (2014)A Comparison Between a Deep Convolutional Neural Network and Radiologists for Classifying Regions of Interest in Mammography.T. Kooi, A. Gubern-Mérida, J. Mordang, R. Mann, R. Pijnappel, K. Schuur, A. den Heeten, and N. Karssemeijer. Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 51-56. Springer, (2016)Breast segmentation in MRI: quantitative evaluation of three methods.A. Gubern-Mérida, L. Wang, M. Kallenberg, R. Marti, H. Hahn, and N. Karssemeijer. Medical Imaging: Image Processing, volume 8669 of SPIE Proceedings, page 86693G. SPIE, (2013)Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation.J. van Vugt, E. Marchiori, R. Mann, A. Gubern-Mérida, N. Moriakov, and J. Teuwen. CoRR, (2018)Multimodal Breast Parenchymal Patterns Correlation Using a Patient-Specific Biomechanical Model.E. García, Y. Diez, O. Díaz, X. Lladó, A. Gubern-Mérida, R. Marti, J. Martí, and A. Oliver. IEEE Trans. Med. Imaging, 37 (3): 712-723 (2018)Automatic Microcalcification Detection in Multi-vendor Mammography Using Convolutional Neural Networks.J. Mordang, T. Janssen, A. Bria, T. Kooi, A. Gubern-Mérida, and N. Karssemeijer. Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 35-42. Springer, (2016)Multi-class Probabilistic Atlas-Based Segmentation Method in Breast MRI.A. Gubern-Mérida, M. Kallenberg, R. Marti, and N. Karssemeijer. IbPRIA, volume 6669 of Lecture Notes in Computer Science, page 660-667. Springer, (2011)Improving Breast Cancer Detection Using Symmetry Information with Deep Learning.Y. Hagos, A. Gubern-Mérida, and J. Teuwen. RAMBO+BIA+TIA@MICCAI, volume 11040 of Lecture Notes in Computer Science, page 90-97. Springer, (2018)Towards Accurate Segmentation of Fibroglandular Tissue in Breast MRI Using Fuzzy C-Means and Skin-Folds Removal.M. Razavi, L. Wang, A. Gubern-Mérida, T. Ivanovska, H. Laue, N. Karssemeijer, and H. Hahn. ICIAP (1), volume 9279 of Lecture Notes in Computer Science, page 528-536. Springer, (2015)