Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Mikael Agn"'
Autor:
Mikael Agn, Koen Van Leemput
Publikováno v:
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures ISBN: 9783030326883
UNSURE/CLIP@MICCAI
UNSURE/CLIP@MICCAI
In this paper we propose a probabilistic model for multi-modal non-linear registration that directly incorporates the mutual information (MI) metric into a demons-like optimization scheme. In contrast to uni-modal registration, where the demons algor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68119b2a3ad25572e6c997870e143d0d
https://doi.org/10.1007/978-3-030-32689-0_5
https://doi.org/10.1007/978-3-030-32689-0_5
Autor:
Per Munck af Rosenschöld, Laura Mancini, Mikael Agn, John Ashburner, Anastasia Papadaki, Michael Lundemann, Ian Law, Koen Van Leemput, Steffi Thust, Oula Puonti
Publikováno v:
Medical Image Analysis
Agn, M, Munck af Rosenschöld, P, Puonti, O, Lundemann, M J, Mancini, L, Papadaki, A, Thust, S, Ashburner, J, Law, I & Van Leemput, K 2019, ' A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning ', Medical Image Analysis, vol. 54, pp. 220-237 . https://doi.org/10.1016/j.media.2019.03.005
Agn, M, Munck Af Rosenschöld, P, Puonti, O, Lundemann, M J, Mancini, L, Papadaki, A, Thust, S, Ashburner, J, Law, I & Van Leemput, K 2019, ' A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning ', Medical Image Analysis, vol. 54, pp. 220-237 . https://doi.org/10.1016/j.media.2019.03.005
Med Image Anal
Agn, M, Munck af Rosenschöld, P, Puonti, O, Lundemann, M J, Mancini, L, Papadaki, A, Thust, S, Ashburner, J, Law, I & Van Leemput, K 2019, ' A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning ', Medical Image Analysis, vol. 54, pp. 220-237 . https://doi.org/10.1016/j.media.2019.03.005
Agn, M, Munck Af Rosenschöld, P, Puonti, O, Lundemann, M J, Mancini, L, Papadaki, A, Thust, S, Ashburner, J, Law, I & Van Leemput, K 2019, ' A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning ', Medical Image Analysis, vol. 54, pp. 220-237 . https://doi.org/10.1016/j.media.2019.03.005
Med Image Anal
In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method combines a contrast-adaptive generative model for whole-brain segmentation
Publikováno v:
Medical Imaging: Image Processing
Agn, M, Law, I, Munck Af Rosenschöld, P & Van Leemput, K 2016, A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients . in SPIE Medical Imaging 2016: Image Processing . vol. 9784, 97841D, SPIE-International Society for Optical Engineering, Proceedings of SPIE-The International Society for Optical Engineering, SPIE Medical Imaging 2016, San Diego, California, United States, 01/03/2016 . https://doi.org/10.1117/12.2216814
Agn, M, Law, I, Munck Af Rosenschöld, P & Van Leemput, K 2016, A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients . in SPIE Medical Imaging 2016: Image Processing . vol. 9784, 97841D, SPIE-International Society for Optical Engineering, Proceedings of SPIE-The International Society for Optical Engineering, SPIE Medical Imaging 2016, San Diego, California, United States, 01/03/2016 . https://doi.org/10.1117/12.2216814
We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which
Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ISBN: 9783319308579
Brainles@MICCAI
Brainles@MICCAI
In this paper, we present a fully automated generative method for brain tumor segmentation in multi-modal magnetic resonance images. The method is based on the type of generative model often used for segmenting healthy brain tissues, where tissues ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb33129e8bb34d012c62eee262777af2
https://doi.org/10.1007/978-3-319-30858-6_15
https://doi.org/10.1007/978-3-319-30858-6_15
Autor:
Agnete Overgaard, Anja Pinborg, Mikael Agn, Susanne Henningsson, Vibe G. Frokjaer, Gitte M. Knudsen, Claus Svarer, Dea S. Stenbæk, Maria Heede, Anna P. Nielsen, Jens D. Mikkelsen, Elisabeth Clare Larsen, Peter S. Jensen, Klaus K. Holst, Hartwig R. Siebner, Sophie da Cunha-Bang, Szabolcs Lehel
Publikováno v:
Biological psychiatry. 78(8)
Background An adverse response to acute and pronounced changes in sex-hormone levels during, for example, the perimenopausal or postpartum period appears to heighten risk for major depression in women. The underlying risk mechanisms remain elusive bu
Publikováno v:
Image Analysis ISBN: 9783319196640
SCIA
SCIA
Accurate tumor segmentation plays an important role in radiosurgery planning and the assessment of radiotherapy treatment efficacy. In this paper we propose a method combining an ensemble of 2D convolutional neural networks for doing a volumetric seg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::878c24482dc7125b61f8bc686be3fc0c
https://doi.org/10.1007/978-3-319-19665-7_17
https://doi.org/10.1007/978-3-319-19665-7_17
Autor:
Liu, Yan1,2, Stojadinovic, Strahinja2, Hrycushko, Brian2, Wardak, Zabi2, Lau, Steven2, Lu, Weiguo2, Yan, Yulong2, Jiang, Steve B.2, Zhen, Xin2,3, Timmerman, Robert2, Nedzi, Lucien2, Gu, Xuejun2 xuejun.gu@utsouthwestern.edu
Publikováno v:
PLoS ONE. 10/6/2017, Vol. 12 Issue 10, p1-17. 17p.
Autor:
Nadeem, Muhammad Waqas1,2 (AUTHOR) muzammil.hussain@umt.edu.pk, Ghamdi, Mohammed A. Al3 (AUTHOR) maeghamdi@uqu.edu.sa, Hussain, Muzammil2 (AUTHOR), Khan, Muhammad Adnan1 (AUTHOR) khalid.masood@lgu.edu.pk, Khan, Khalid Masood1 (AUTHOR), Almotiri, Sultan H.3 (AUTHOR) shmotiri@uqu.edu.sa, Butt, Suhail Ashfaq4 (AUTHOR) suhail.ashfaq@ue.edu.pk
Publikováno v:
Brain Sciences (2076-3425). Feb2020, Vol. 10 Issue 2, p118. 1p.
Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke & Traumatic Brain Injuries; 2016, pI-IX, 9p
Publikováno v:
Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings; 2015, p201-211, 11p