Search Results for author:
Found 5 papers, 2 papers with code
Deep segmentation networks predict survival of non-small cell lung cancer
Here we show that CNN trained to perform the tumor segmentation task, with no other information than physician contours, identify a rich set of survival-related image features with remarkable prognostic value.
ZerNet: Convolutional Neural Networks on Arbitrary Surfaces via Zernike Local Tangent Space Estimation
In this paper, we propose a novel formulation to extend CNNs to two-dimensional (2D) manifolds using orthogonal basis functions, called Zernike polynomials.
Embedded Spectral Descriptors: Learning the point-wise correspondence metric via Siamese neural networks
In this paper, it is proposed a method to improve the similarity metric of spectral descriptors for correspondence matching problems.
Wall Stress Estimation of Cerebral Aneurysm based on Zernike Convolutional Neural Networks
The problem is well-known to be of a paramount clinical importance, but yet, traditional ConvNets cannot be applied due to the manifold structure of the data, neither does the state-of-the-art geometric ConvNets perform well.
Noise-to-Norm Reconstruction for Industrial Anomaly Detection and Localization
In this study, a reconstruction-based method using the noise-to-norm paradigm is proposed, which avoids the invariant reconstruction of anomalous regions.
