We propose a novel deep neural network based on Transformer, named TransHRNet, which connects the different resolution streams in parallel and repeatedly ...
In this paper, we aim to connect the different resolution streams in parallel and propose a novel network, named Transformer based High Resolution Network ( ...
In this paper, we aim to connect the different resolution streams in parallel and propose a novel network, named Transformer based High Resolution Network ( ...
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What is 3D medical image segmentation?
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Medical image segmentation primarily utilizes a hybrid model consisting of a Convolutional Neural Network and sequential Transformers.
Feb 4, 2024 · To address this issue, we propose a novel series-parallel network that combines convolution and self-attention for 3D medical image segmentation ...
The transformer blocks in UNETR are mainly used in the encoder to extract fixed global representations and then are merged at multiple resolutions with a CNN- ...
Medical image segmentation is crucial for lesion localization and surgical navigation. Recent advancements in medical image segmentation have been driven by ...
In this paper, we propose a 3D medical image segmentation approach, named ... Each EPA block performs two tasks using parallel attention modules with ...
Apr 15, 2024 · Abstract:The adoption of Vision Transformers (ViTs) based architectures represents a significant advancement in 3D Medical Image (MI) ...
Missing: parallel | Show results with:parallel
Duration: 4:50
Posted: Nov 1, 2022
Posted: Nov 1, 2022
Missing: parallel | Show results with:parallel