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Found 6 papers, 2 papers with code
Classification of Tumor Histology via Morphometric Context
Image-based classification of tissue histology, in terms of different components (e. g., normal signature, categories of aberrant signatures), provides a series of indices for tumor composition.
Classification of Histology Sections via Multispectral Convolutional Sparse Coding
Image-based classification of histology sections plays an important role in predicting clinical outcomes.
NaroNet: Discovery of tumor microenvironment elements from highly multiplexed images
Many efforts have been made to discover tumor-specific microenvironment elements (TMEs) from immunostained tissue sections.
Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillation
The success of automated medical image analysis depends on large-scale and expert-annotated training sets.
Learning to Generalize over Subpartitions for Heterogeneity-aware Domain Adaptive Nuclei Segmentation
Annotation scarcity and cross-modality/stain data distribution shifts are two major obstacles hindering the application of deep learning models for nuclei analysis, which holds a broad spectrum of potential applications in digital pathology.
Seeing Unseen: Discover Novel Biomedical Concepts via Geometry-Constrained Probabilistic Modeling
Machine learning holds tremendous promise for transforming the fundamental practice of scientific discovery by virtue of its data-driven nature.
