Multi-tissue Nucleus Segmentation
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Benchmarks
Most implemented
U-Net: Convolutional Networks for Biomedical Image Segmentation
Mask R-CNN
Fully Convolutional Networks for Semantic Segmentation
HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images
Rotation equivariant vector field networks
Papers
MRL: Learning to Mix with Attention and Convolutions
In this paper, we present a new neural architectural block for the vision domain, named Mixing Regionally and Locally (MRL), developed with the aim of effectively and efficiently mixing the provided input features. We bi…
Histopathological SegmentationInductive BiasMulti-tissue Nucleus Segmentationobject-detection+1SONNET: A Self-Guided Ordinal Regression Neural Network for Segmentation and Classification of Nuclei in Large-Scale Multi-Tissue Histology Images
Automated nuclei segmentation and classification are the keys to analyze and understand the cellular characteristics and functionality, supporting computer-aided digital pathology in disease diagnosis. However, the task …
ClassificationMulti-tissue Nucleus SegmentationNuclear SegmentationNuclei Classification+2PointNu-Net: Keypoint-assisted Convolutional Neural Network for Simultaneous Multi-tissue Histology Nuclei Segmentation and Classification
Automatic nuclei segmentation and classification play a vital role in digital pathology. However, previous works are mostly built on data with limited diversity and small sizes, making the results questionable or mislead…
ClassificationDiversityInstance SegmentationKeypoint Estimation+3Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images
Histology images are inherently symmetric under rotation, where each orientation is equally as likely to appear. However, this rotational symmetry is not widely utilised as prior knowledge in modern Convolutional Neural …
Breast Tumour ClassificationColorectal Gland Segmentation:Multi-tissue Nucleus SegmentationNuclear Segmentation+1Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis
Rotation-invariance is a desired property of machine-learning models for medical image analysis and in particular for computational pathology applications. We propose a framework to encode the geometric structure of the …
BIG-bench Machine LearningBreast Tumour ClassificationColorectal Gland Segmentation:Data Augmentation+4CIA-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. While it still remains challenging be…
Instance SegmentationMulti-tissue Nucleus SegmentationSegmentationSemantic Segmentation