In this work, the utility and accuracy of the statistical detection algorithms for the detection of mitosis on histopathological images have been ...
The results indicate that the MF is the best algorithm on mitosis detection among the implemented algorithms. In this work, the utility and accuracy of the ...
Later, the three statistical detection algorithms have been implemented in this work, namely matched filtering (MF), constrained energy minimization (CEM) and ...
Later, the three statistical detection algorithms have been implemented in this work, namely matched filtering (MF), constrained energy minimization (CEM) and ...
Mar 18, 2021 · This work proposes deep CNN based multi-phase mitosis detection framework “MP-MitDet” for mitotic nuclei identification in breast cancer histopathological ...
We propose a generalizable and robust mitosis detection algorithm (called FMDet), which is independently tested on multicenter breast histopathological images.
We present a multistage mitotic-cell-detection method based on Faster region convolutional neural network (Faster R-CNN) and deep CNNs.
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How do you detect mitosis?
How can calculations of the mitotic index be used in the prediction and or diagnosis of cancer?
We use deep max-pooling convolutional neural networks to detect mitosis in breast histology images. The networks are trained to classify each pixel in the ...
Jan 20, 2022 · The four major stages in the proposed method are, (i) Image color normalization, (ii) Candidate cell detection, (iii) Context preserving data ...
Automated mitosis detection methods work by a model trained on annotated data. The model can classify nuclei from new histopathological slices as mitotic and ...