In this paper, we try to solve this problem from a new perspective, that is, introducing self-distillation mechanism to fully utilize the features extracted ...

We apply the self-distillation to tiny tissues segmentation. This method can be easily integrated into the existing encoder-decoder structured network to ...

In this paper, we try to solve this problem from a new perspective, that is, introducing self-distillation mechanism to fully utilize the features extracted ...

Experiments show that the performance of these models has been improved, which proves that the method is a general method and can be widely used in the ...

This technique incorporates noise removal functions (High-pass and Median filters), segmentation and morphological operations. This method is generally used to ...

Apr 19, 2024 · Latent Diffusion Models (LDMs) can generate high-fidelity images from noise, offering a promising approach for augmenting histopathology ...

Enhancing tiny tis- sues segmentation via self-distillation. In: 2020 IEEE International Conference · on Bioinformatics and Biomedicine (BIBM). IEEE, pp. 934 ...

This paper innovatively proposes a novel retinal vessel segmentation network framework based on self-distillation and implicit neural representation

Unlike the classic semi-supervised setting, the burn-in phase in DIOD is applied using noisy segmentation labels. We examine in section 5.3 the effect of ...

The input X initially undergoes 3 pretrained ResNet50 blocks to generate generic features and extract spatial information. To enhance the segmentation ...