Multi-tissue Nucleus Segmentation
10 papers with code • 3 benchmarks • 3 datasets
Latest papers with no code
MRL: Learning to Mix with Attention and Convolutions
To achieve an efficient mix, we exploit the domain-wide receptive field provided by self-attention for regional-scale mixing and convolutional kernels restricted to local scale for local-scale mixing.
CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation
Accurate segmenting nuclei instances is a crucial step in computer-aided image analysis to extract rich features for cellular estimation and following diagnosis as well as treatment.
Micro-Net: A unified model for segmentation of various objects in microscopy images
Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images.
Learning Steerable Filters for Rotation Equivariant CNNs
In many machine learning tasks it is desirable that a model's prediction transforms in an equivariant way under transformations of its input.