Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Isosalo, A. (Antti)"'
Autor:
Nykänen, O. (Olli), Nevalainen, M. (Mika), Casula, V. (Victor), Isosalo, A. (Antti), Inkinen, S. I. (Satu I.), Nikki, M. (Marko), Lattanzi, R. (Riccardo), Cloos, M. A. (Martijn A.), Nissi, M. J. (Mikko J.), Nieminen, M. T. (Miika T.)
Background: Magnetic resonance fingerprinting (MRF) is a method to speed up acquisition of quantitative MRI data. However, MRF does not usually produce contrast-weighted images that are required by radiologists, limiting reachable total scan time imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2423::08ef094de4d056987f8719df09ddb71b
http://urn.fi/urn:nbn:fi-fe2023063068685
http://urn.fi/urn:nbn:fi-fe2023063068685
Autor:
Nykänen, O. (Olli), Isosalo, A. (Antti), Inkinen, S. (Satu), Casula, V. (Victor), Nevalainen, M. (Mika), Lattanzi, R. (Riccardo), Cloos, M. (Martijn), Nissi, M. (Mikko), Nieminen, M. T. (Miika T.)
Synopsis In this study, deep convolutional neural networks (DCNN) are used to synthesize contrast-weighted magnetic resonance (MR) images from quantitative parameter maps of the knee joint obtained with magnetic resonance fingerprinting (MRF). Traini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2423::c8fab314fed38eee6e3ba6976ee788ae
http://urn.fi/urn:nbn:fi-fe2023063068891
http://urn.fi/urn:nbn:fi-fe2023063068891
Autor:
Isosalo, A. (Antti), Mustonen, H. (Henrik), Turunen, T. (Topi), Ipatti, P. S. (Pieta S.), Reponen, J. (Jarmo), Nieminen, M. T. (Miika T.), Inkinen, S. I. (Satu I.)
In this work, we study convolutional neural network encoder-decoder architectures with pre-trained encoder weights for breast mass segmentation from digital screening mammograms. To automatically detect breast cancer, one fundamental task to achieve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2423::4d2e85b5633823a455c06c97bd46099b
http://urn.fi/urn:nbn:fi-fe2022061747588
http://urn.fi/urn:nbn:fi-fe2022061747588