Nov 23, 2021 � To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection.
Dec 18, 2020 � Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease.
From: Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer's disease�...
Apr 27, 2024 � Conclusion The relevance maps highlighted atrophy in regions that we had hypothesized a priori. This strengthens the comprehensibility of the�...
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A review of the application of three-dimensional convolutional neural networks for the diagnosis of Alzheimer's disease using neuroimaging � Alzheimer's MRI�...
To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps. Across three independent datasets, group separation�...
To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection. Results.
Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer's disease. Martin Dyrba.
This project contains all code to learn a convolutional neural network model to detect Alzheimer's disease and visualize contributing brain regions with�...
Improving 3D convolutional neural net- work comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease; 2020.