- Importance of Equivariance in image reconstruction and denoising🔍
- Spherical CNN for Medical Imaging Applications🔍
- Spherical convolutional neural networks can improve brain ...🔍
- Equivariant Spherical CNN for Data Efficient and High|Performance ...🔍
- Scalable spherical CNNs for scientific applications🔍
- Spherical convolutional neural networks🔍
- How Can Spherical CNNs Benefit ML|Based Diffusion MRI ...🔍
- The Role of Geometry in Convolutional Neural Networks for Medical ...🔍
Spherical CNN for Medical Imaging Applications
Importance of Equivariance in image reconstruction and denoising
Title:Spherical CNN for Medical Imaging Applications: Importance of Equivariance in image reconstruction and denoising ; Subjects: Image and ...
Spherical CNN for Medical Imaging Applications - NCBI
Abstract. This work highlights the significance of equivariant networks as efficient and high-performance approaches for tomography applications. Our study ...
Importance of Equivariance in image reconstruction and denoising
We evaluate the efficacy of equivariant spherical CNNs (SCNNs) for 2- and 3- dimensional medical imaging problems. Our results demonstrate ...
Spherical convolutional neural networks can improve brain ...
Spherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data ... Diffusion magnetic resonance imaging is sensitive ...
Equivariant Spherical CNN for Data Efficient and High-Performance ...
We will show variational invariance of training set play a key role on the performance of CNNs in medical imaging applications and therefore approaches such as.
Scalable spherical CNNs for scientific applications - Google Research
This motivates the application of spherical CNNs because of their rotation equivariance. However, molecules are not defined as signals on the ...
Spherical convolutional neural networks: Stability to perturbations in
Spherical convolutional neural networks (Spherical CNNs) learn nonlinear representations from 3D data by exploiting the data structure and have shown ...
How Can Spherical CNNs Benefit ML-Based Diffusion MRI ...
This paper demonstrates spherical convolutional neural networks (S-CNN) offer distinct advantages over conventional fully- connected networks (FCN) at ...
The Role of Geometry in Convolutional Neural Networks for Medical ...
various applications in medical imaging. Elyasi and Moghadam12 utilized TDA ... These studies highlight the potential of. TDA-CNN combinations in medical imaging.
Spherical Convolutional Neural Networks for Survival Rate ...
Methods: In the first stage, the tumor is segmented from the CT image of the lungs. Here, we use a deep-learning-based method that entails a ...
Spherical U-Net on Cortical Surfaces: Methods and Applications
However, unlike in the Euclidean space, the shapes of many structures in medical imaging have a spherical topology in a manifold space, e.g., brain cortical or ...
The Role of Geometry in Convolutional Neural Networks for Medical ...
Just as topology has contributed tools to improve CNN performance, so too have a few fields of geometry, and many of these applications involve the addition of ...
How can spherical CNNs benefit ML-based diffusion MRI parameter ...
Abstract:This paper demonstrates spherical convolutional neural networks (S-CNN) offer distinct advantages over conventional fully-connected ...
People often reproach deep neural network models their lack of interpretability. In particular for medical applications, being able to ...
A spherical convolutional neural network for white matter structure ...
Diffusion MRI (dMRI) is an imaging modality that exploits the interactions of diffusing water molecules with the surrounding tissue micro- ...
Successful applications have been demonstrated in tasks such as 3D shape analysis [16, 18], medical imaging [42, 3], satellite/aerial imaging [13, 21],.
12: Spherical U-Net on Cortical Surfaces: Methods and Applications
By introducing a new filter type and adapting the known methods of CNN, this paper offers a novel alternative to the two approaches commonly used for spherical ...
Grid Based Spherical CNN for Object Detection from Panoramic ...
Recently proposed spherical convolutional neural networks (SCNNs) have shown advantages over conventional planar CNNs on classifying ...
A spherical convolutional neural network for white matter structure ...
In this work, we propose a spherical CNN model with fully spectral domain convolutional and non-linear layers. It provides rotational invariance ...
A Spherical Convolutional Neural Network for White Matter Structure ...
... Spherical Deconvolution with Limited Single Shell DW-MRI. V. Nath, S. Pathak, K. Schilling, W. Schneider, B. Landman. Medical Imaging: Image Processing 2020.