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Apr 6, 2024 · In this section, we propose a GAN-nested model to augment multimodal brain tumor images, providing additional tumor label maps for training ...
In this paper, we propose a segmentation method, which involves a GAN-nested model and an improved UNet. ... Extensive experimental results prove that the ...
In this paper, we propose an automatic brain tumor segmentation algorithm based on a 22-layers deep, three-dimensional Convolutional Neural Network (CNN) ...
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Jul 22, 2024 · The broad use of multi-modal MRI images in the segmentation of brain tumors has been facilitated by advancements in MRI technology. This method ...
The precise segmentation of brain tumor images is a vital step towards accurate diagnosis and effective treatment of brain tumors.
In this paper, we present a fully automatic brain tumor segmentation method based on Deep Neural Networks (DNNs).
Jan 2, 2024 · This section presents a detailed review and analysis of lymphoma segmentation, including a summary of state-of-the-art networks based on multi-modal ...
Apr 26, 2023 · This research work provides an efficient method for brain Tumor segmentation based on the Improved Residual Network (ResNet).
Missing: Multimodal | Show results with:Multimodal
May 25, 2021 · Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images. Ramin Ranjbarzadeh,; Abbas ...
This paper proposes a method based on Deep Learning, using deep convolution networks based on the U-Net model that can provide a segmentation that is both ...