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pro vyhledávání: '"358"'
Independent component analysis (ICA) of multi-subject functional magnetic resonance imaging (fMRI) data has proven useful in providing a fully multivariate summary that can be used for multiple purposes. ICA can identify patterns that can discriminat
Externí odkaz:
http://arxiv.org/abs/2211.07374
The thighbone is the largest bone supporting the lower body. If the thighbone fracture is not treated in time, it will lead to lifelong inability to walk. Correct diagnosis of thighbone disease is very important in orthopedic medicine. Deep learning
Externí odkaz:
http://arxiv.org/abs/2210.10998
A fully automated system for interpreting abdominal computed tomography (CT) scans with multiple phases of contrast enhancement requires an accurate classification of the phases. This work aims at developing and validating a precise, fast multi-phase
Externí odkaz:
http://arxiv.org/abs/2203.11206
Autor:
Zhang, Guokai, Shen, Xiaoang, Luo, Ye, Luo, Jihao, Wang, Zeju, Wang, Weigang, Zhao, Binghui, Lu, Jianwei
Automatic segmentation of the prostate cancer from the multi-modal magnetic resonance images is of critical importance for the initial staging and prognosis of patients. However, how to use the multi-modal image features more efficiently is still a c
Externí odkaz:
http://arxiv.org/abs/2011.03908
Publikováno v:
Artificial Intelligence for COVID-19. Studies in Systems, Decision and Control, vol 358. 2021, Springer, Cham
Clinicians in the frontline need to assess quickly whether a patient with symptoms indeed has COVID-19 or not. The difficulty of this task is exacerbated in low resource settings that may not have access to biotechnology tests. Furthermore, Tuberculo
Externí odkaz:
http://arxiv.org/abs/2007.08223
We present a dataset with models of 14 articulated objects commonly found in human environments and with RGB-D video sequences and wrenches recorded of human interactions with them. The 358 interaction sequences total 67 minutes of human manipulation
Externí odkaz:
http://arxiv.org/abs/1806.06465
In this paper we present a novel technique of registering 3D images across pose. In this context, we have taken into account the images which are aligned across X, Y and Z axes. We have first determined the angle across which the image is rotated wit
Externí odkaz:
http://arxiv.org/abs/1309.3425