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pro vyhledávání: '"39"'
Autor:
De Ma, Zhifei Dai, Oren Solomon, Jianwen Luo, Yonina C. Eldar, Ruud J. G. van Sloun, Yi Zhang, He Qiong, Regev Cohen, Yi Yang
Publikováno v:
IEEE Transactions on Medical Imaging
IEEE Transactions on Medical Imaging, 39(4):8836615, 1051-1063. Institute of Electrical and Electronics Engineers
IEEE Transactions on Medical Imaging, 39(4):8836615, 1051-1063. Institute of Electrical and Electronics Engineers
Contrast enhanced ultrasound is a radiation-free imaging modality which uses encapsulated gas microbubbles for improved visualization of the vascular bed deep within the tissue. It has recently been used to enable imaging with unprecedented subwavele
Autor:
Zhao, Yifan, Zhao, Yitian, Durongbhan, Pholpat, Chen, Liangyu, Liu, Jiang, Billings, S. A., Zis, Panagiotis, Unwin, Zoe C., De Marco, Matteo, Venneri, Annalena, Blackburn, Daniel J., Sarrigiannis, Ptolemaios G.
Publikováno v:
IEEE Transactions on Medical Imaging
Since age is the most significant risk factor for the development of Alzheimer’s disease (AD), it is important to understand the effect of normal ageing on brain network characteristics before we can accurately diagnose the condition based on infor
Autor:
Hancong Xu, Julian Bert, Christoph Lerche, Philipp Lohmann, Liliana Caldeira, Nadim Jon Shah, Elena Rota Kops, Michaela Gaens, Mirjam Lenz, Lutz Tellmann, B. H. Ma, Jürgen Scheins, Uwe Pietrzyk
Publikováno v:
IEEE transactions on medical imaging 39(1), 140-151 (2020). doi:10.1109/TMI.2019.2921872
Accurate scatter correction is essential for qualitative and quantitative PET imaging. Until now, scatter correction based on Monte Carlo simulation (MCS) has been recognized as the most accurate method of scatter correction for PET. However, the maj
Autor:
Dan Wang, Ahmed H. Tewfik
Publikováno v:
IEEE Transactions on Medical Imaging. 31:924-937
Restricted visualization of the surgical field is one of the most critical challenges for minimally invasive surgery (MIS). Current intraoperative visualization systems are promising. However, they can hardly meet the requirements of high resolution
Publikováno v:
IEEE Transactions on Medical Imaging. 29:1714-1729
We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps. The resulting inference algorithms rely on pairwise registrations between the test image an