Objective: In this study, we propose a new method that can efficiently and accurately segment intervertebral discs from multi-modal MR spine images, providing a reproducible usage scheme for the diagnosis of spinal disorders. Methods: We suggest a network structure called MLP-Res-Unet that reduces...
3 | Methods In this study, the PointMLP network, known for its exceptional performance in 3D point cloud classification tasks, is applied to automatically extract medical feature points on the pelvic sur- face. Typically, PointMLP is used for classification tasks, where it is designed to find ...
“broken” neural network and quantitatively analyzing the problem behind this broken network. The second part involves exploring two solutions in literature for fixing this “broken” neural network, and then subsequently implementing them to improve the performance and training of this network. In ord...
The environment was configured with Python 3, and the following libraries were employed for data processing, model development, and evaluation: 4.1. Detailed Description and Analysis We have provided a comparative analysis of the performance of a one-dimensional convolutional neural network (1D-CNN)...
This enables the network to capture diverse geometric structures and generate a robust global descriptor. Our proposed method undergoes extensive evaluation on the Oxford outdoor dataset and three in-house datasets, demonstrating an improvement of at least 2% over previous methods on the newly proposed...
the MLP framework, and totest your implementation. The objective of the second part is to explore different approaches to integrating information in convolutional networks: pooling, strided convolutions, and dilated convolutions. Carrying out larger convolutional network experiments using the MLP framework...
When using MLP regression models, some method for estimating the generalisation ability is required to identify badly over and underfitted models. If data is limited, it may be impossible to spare sufficient data for a test set, and leave-one-out crossvalidation may be considered as an alternat...
First, we transform the users’ information into vectors and use SVD method to reduce dimensions and then learn the preferences and interests of all users based on the improved kernel function and map them to the network; finally, we predict the user’s rating for the items through the ...
The ablation study of 12 cases is carried out on the architecture by changing the network's layer architecture and values of hyper-parameters. Finally, this proposed ECgMLP methodology provides a comprehensive framework for achieving the best result on the processed dataset. In the result analysis,...
Therefore, a lightweight medical diagnosis network CTMLP based on convolutions and multi-layer perceptrons (MLPs) is proposed for the diagnosis of COVID-19. The previous self-supervised algorithms are based on CNNs and VITs, and the effectiveness of such algorithms for MLPs is not yet known....