SOTAVerified

Mitosis Detection

Papers

Showing 26–47 of 47 papers

TitleStatusHype
Domain Adaptive Cascade R-CNN for MItosis DOmain Generalization (MIDOG) Challenge—0
Sk-Unet Model with Fourier Domain for Mitosis Detection—0
Two-step Domain Adaptation for Mitosis Cell Detection in Histopathology Images—0
Positive-unlabeled Learning for Cell Detection in Histopathology Images with Incomplete Annotations—0
Mitosis Detection Under Limited Annotation: A Joint Learning Approach—0
Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy via Likelihood Map Estimation by 3DCNNCode0
Virtual staining for mitosis detection in Breast Histopathology—0
Semi-supervised estimation of event temporal length for cell event detection—0
Joint Multi-frame Detection and Segmentation for Multi-cell Tracking—0
Advanced Deep Convolutional Neural Network Approaches for Digital Pathology Image Analysis: a comprehensive evaluation with different use cases—0
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks—0
Inferring the ground truth through crowdsourcing—0
Leveraging Unlabeled Whole-Slide-Images for Mitosis Detection—0
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge—0
Replication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographsCode0
SlideRunner - A Tool for Massive Cell Annotations in Whole Slide ImagesCode0
Domain-adversarial neural networks to address the appearance variability of histopathology images—0
Mathematical Imaging Methods for Mitosis Analysis in Live-Cell Phase Contrast Microscopy—0
A Unified Framework for Tumor Proliferation Score Prediction in Breast HistopathologyCode0
Mitosis Detection in Intestinal Crypt Images with Hough Forest and Conditional Random Fields—0
Assessment of algorithms for mitosis detection in breast cancer histopathology images—0
Multispectral Spatial Characterization: Application to Mitosis Detection in Breast Cancer Histopathology—0
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