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Found 5 papers, 3 papers with code
Multi-view Cardiac Image Segmentation via Trans-Dimensional Priors
We evaluate our proposed method on the Multi-Disease, Multi-View & Multi-Center Right Ventricular Segmentation in Cardiac MRI (M&Ms-2) dataset, where our method outperforms state-of-the-art methods in segmenting cardiac regions of interest in both short-axis and long-axis images.
MOAB: Multi-Modal Outer Arithmetic Block For Fusion Of Histopathological Images And Genetic Data For Brain Tumor Grading
We propose a novel Multi-modal Outer Arithmetic Block (MOAB) based on arithmetic operations to combine latent representations of the different modalities for predicting the tumor grade (Grade \rom{2}, \rom{3} and \rom{4}).
Crop and Couple: cardiac image segmentation using interlinked specialist networks
Diagnosis of cardiovascular disease using automated methods often relies on the critical task of cardiac image segmentation.
Automated segmentation of rheumatoid arthritis immunohistochemistry stained synovial tissue
The model obtains a DICE score of 0. 865 and successfully segments different types of IHC staining, as well as dealing with variance in colours, intensity and common WSIs artefacts from the different clinical centres.
TSFD-Net: Tissue specific feature distillation network for nuclei segmentation and classification
Nuclei segmentation and classification of hematoxylin and eosin-stained histology images is a challenging task due to a variety of issues, such as color inconsistency that results from the non-uniform manual staining operations, clustering of nuclei, and blurry and overlapping nuclei boundaries.
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