We propose a novel multi-task learning network that leverages the correlation between the segmentation and classification networks to enhance the performance ...
Nov 20, 2023 · We propose a novel multi-task learning network that leverages the correlation between the segmentation and classification networks to enhance the performance ...
Jun 4, 2024 · Specifically, the classification task takes the tumor region images extracted from the segmentation network's output as input, effectively ...
To address above challenges, we propose a novel multi-task learning network that leverages the correlation between the segmentation and classification networks ...
In this paper, a selected multi-scale attention network is proposed to segment tumor cells, blood vessels, nerves, islets and ducts in pancreatic pathological ...
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In this paper, we propose a novel multi-task learning framework for joint segmentation and classification of tumors in ABUS images. The proposed framework ...
Jun 22, 2024 · This work proposes a semi-supervised multi-task network (SSM-Net) to leverage unlabeled and labeled EUS images for joint pancreatic lesion classification and ...
This paper propose a novel Multi-modal Fusion and Calibration Networks (MFCNet) for tumor segmentation based on three-dimensional PET-CT images.
Aug 7, 2024 · The model achieved better segmentation performance in abdominal organs, cardiovascular structures, and brain tumor segmentation experiments.
In this article, we present AX-Unet, a deep learning framework incorporating a modified atrous spatial pyramid pooling module to learn the location information.