Mar 2, 2023 · We present a prototypical few-shot segmentation approach for ischemic lesion segmentation using only one annotated sample during training.
self-supervised few-shot learning for ischemic stroke lesion - IEEE Xplore
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The proposed approach leverages a novel self-supervised train- ing mechanism that is tailored to the task of ischemic stroke lesion segmentation by exploiting ...
Oct 22, 2024 · This study proposes an ischemic stroke lesion segmentation technique based on a small number of labeled samples, which only requires one labeled sample during ...
Mar 2, 2023 · The proposed approach leverages a novel self-supervised training mechanism that is tailored to the task of ischemic stroke lesion segmentation ...
The proposed approach leverages a novel self-supervised training mechanism that is tailored to the task of ischemic stroke lesion segmentation by exploiting ...
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What is few shot learning in medical image segmentation?
What is stroke segmentation?
An automatic ischemic stroke segmentation system using few-shot learning is proposed. The proposed system selects only slices with lesions and excludes ...
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation. Luca Tomasetti; Stine Hansen; Mahdieh Khanmohammadi; Kjersti Engan; Liv Jorunn ...
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation ... Precise ischemic lesion segmentation plays an essential role in improving diagnosis ...
In [41] , the authors proposed a self-supervised few-shot learning model for segmenting ischemic stroke lesions using CT scans. The model uses a two-stage ...
Feb 27, 2024 · In this paper, we propose a few-shot learning strategy and integrate it with a base convolutional neural network model, which utilizes a self- ...