Search Results for author:
Found 5 papers, 3 papers with code
Evaluation of Multi-indicator And Multi-organ Medical Image Segmentation Models
As a result, MIMO offers detailed information on the segmentation of each organ in each sample, thereby aiding developers in analyzing and improving the model.
ShuffleMix: Improving Representations via Channel-Wise Shuffle of Interpolated Hidden States
Inspired by good robustness of alternative dropout strategies against over-fitting on limited patterns of training samples, this paper introduces a novel concept of ShuffleMix -- Shuffle of Mixed hidden features, which can be interpreted as a kind of dropout operation in feature space.
An image segmentation algorithm based on multi-scale feature pyramid network
Medical image segmentation is particularly critical as a prerequisite for relevant quantitative analysis in the treatment of clinical diseases.
SECP-Net: SE-Connection Pyramid Network of Organ At Risk Segmentation for Nasopharyngeal Carcinoma
SECP-Net extracts global and multi-size information flow with se connection (SEC) modules and a pyramid structure of network for improving the segmentation performance, especially that of small organs.
PARN: Position-Aware Relation Networks for Few-Shot Learning
However, due to the inherent local connectivity of CNN, the CNN-based relation network (RN) can be sensitive to the spatial position relationship of semantic objects in two compared images.
