Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2021; 24th International C Marleen de Bruijne,Philippe C. Cattin,Caroli

BUDGE

屈尊

Yourself

helper-T-cells

peritonitis

Hallowed

Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-supervised Learningtion). We show that high accuracy can be achieved by simply propagating the 2D slice segmentation with an affinity matrix between consecutive slices, which can be learnt in a self-supervised manner, namely slice reconstruction. Specifically, we compare our proposed framework, termed as ., with super

vasospasm

Self-supervised Longitudinal Neighbourhood Embeddinging this data via machine learning generally requires a large number of ground-truth labels, which are often missing or expensive to obtain. Reducing the need for labels, we propose a self-supervised strategy for representation learning named Longitudinal Neighborhood Embedding (LNE). Motivated by c

條街道往前推

overreach

CHIDE

Lesion-Based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images to learn feature representations from unlabeled images. However, unlike natural images, the application of contrastive learning to medical images is relatively limited. In this work, we propose a self-supervised framework, namely lesion-based contrastive learning for automated diabetic retinopathy