Mitosis Detection
12 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Latest papers with no code
Supporting Mitosis Detection AI Training with Inter-Observer Eye-Gaze Consistencies
We assessed the efficacy of such eye-gaze labels by training Convolutional Neural Networks (CNNs) and comparing their performance to those trained with ground truth annotations and a heuristic-based baseline.
Evaluation of the mitotic score of invasive breast carcinomas on digital slide: development and contribution of a mitosis detection algorithm
Its determination requires the evaluation of the mitotic score (MS) which is subject to low intra- and inter-observer reproducibility.
Improving mitosis detection on histopathology images using large vision-language models
In certain types of cancerous tissue, mitotic count has been shown to be associated with tumor proliferation, poor prognosis, and therapeutic resistance.
Fine-Grained Hard Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset
Making histopathology image classifiers robust to a wide range of real-world variability is a challenging task.
Challenging mitosis detection algorithms: Global labels allow centroid localization
Mitotic activity is a crucial proliferation biomarker for the diagnosis and prognosis of different types of cancers.
Multi tasks RetinaNet for mitosis detection
However, due to the variability of mitotic cell morphology, it is a highly challenging task to detect mitotic cells in tumor tissues.
Mitosis Detection, Fast and Slow: Robust and Efficient Detection of Mitotic Figures
Counting of mitotic figures is a fundamental step in grading and prognostication of several cancers.
Detecting Mitoses with a Convolutional Neural Network for MIDOG 2022 Challenge
This work presents a mitosis detection method with only one vanilla Convolutional Neural Network (CNN).
Mitosis domain generalization in histopathology images -- The MIDOG challenge
The goal of the MICCAI MIDOG 2021 challenge has been to propose and evaluate methods that counter this domain shift and derive scanner-agnostic mitosis detection algorithms.
Robust Multi-Domain Mitosis Detection
Domain variability is a common bottle neck in developing generalisable algorithms for various medical applications.
