Fatima Masoud Al-Amouri, Manal Badrasawi
Taste alteration and its relationship with nutritional status among cancer patients receiving chemotherapy, cross-sectional study
PloS one
realm medical image analysis cost associated acquiring accurately labeled data prohibitively high address issue label scarcity semisupervised learning methods employed utilizing unlabeled data alongside limited set labeled data paper presents novel semisupervised medical segmentation framework dcclnet deep consistency collaborative learning unet grounded deep consistent colearning framework synergistically integrates consistency learning feature input perturbations coupled collaborative training cnn convolutional neural networks vit vision transformer capitalize learning advantages offered two distinct paradigms feature perturbation involves application auxiliary decoders varied feature disturbances main cnn backbone enhancing robustness cnn backbone consistency constraints generated auxiliary main decoders input perturbation employs mt mean teacher architecture wherein main network serves student model guided teacher model subjected input perturbations collaborative training aims improve accuracy main networks encouraging mutual learning cnn vit experiments conducted publicly available datasets acdc automated cardiac diagnosis challenge prostate datasets yielded dice coefficients 0890 0812 respectively additionally comprehensive ablation studies performed demonstrate effectiveness methodological contribution study