( en | de | ru )

 

Disambiguation of "Lalande, Alain"

Author of the publication

copydeleteadd this publication to your clipboard
A deep learning approach for the segmentation of myocardial diseases.

, , , , , and . ICPR, page 4544-4551. IEEE, (2020)

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.

Julia Lalande

Jean-Yves Lalande

Jean-François Lalande

Jean-Yves Lalande

Alain Schifferli

 

Other publications of authors with the same name

Semi-automated labelling of medical images: benefits of a collaborative work in the evaluation of prostate cancer in MRI., , , , and . CoRR, (2017)Markovian method for 2D, 3D and 4D segmentation of MRI., , , , and . ICIP, page 3012-3015. IEEE, (2008)GANs for Medical Image Synthesis: An Empirical Study., , and . CoRR, (2021)Segmentation-Free Estimation of Aortic Diameters from MRI Using Deep Learning., , , and . M&Ms and EMIDEC/STACOM@MICCAI, volume 12592 of Lecture Notes in Computer Science, page 166-174. Springer, (2020)Automatic Segmentation of Histological Images of Mouse Brains., , , , and . Algorithms, 16 (12): 553 (2023)Automatic classification of tissues using T1 and T2 relaxation times from prostate MRI: A step towards generation of PET/MR attenuation map., , , and . ICIP, page 1185-1189. IEEE, (2015)Comparison of CNN Fusion Strategies for Left Ventricle Segmentation from Multi-modal MRI., , , and . FIMH, volume 13958 of Lecture Notes in Computer Science, page 265-273. Springer, (2023)A 4D Patient-Specific Modelling of the Thoracic Aorta from Cine-MR Images., , , , , and . SITIS, page 269-276. IEEE Computer Society, (2011)Automatic deep learning-based myocardial infarction segmentation from delayed enhancement MRI., , , , , , , , and . Comput. Medical Imaging Graph., (2022)Deep Learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge., , , , , , , , , and 23 other author(s). CoRR, (2021)