Differentiable optimization layers enhance GNN-based mitosis detection [PDF]
Scientific Reports, 2023 Automatic mitosis detection from video is an essential step in analyzing proliferative behaviour of cells. In existing studies, a conventional object detector such as Unet is combined with a link prediction algorithm to find correspondences between ...
Haishan Zhang +2 more
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Breast cancer survival prediction using an automated mitosis detection pipeline [PDF]
The Journal of Pathology: Clinical ResearchMitotic count (MC) is the most common measure to assess tumor proliferation in breast cancer patients and is highly predictive of patient outcomes. It is, however, subject to inter‐ and intraobserver variation and reproducibility challenges that may ...
Nikolas Stathonikos +6 more
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Mitosis detection in histopathological images using customized deep learning and hybrid optimization algorithms. [PDF]
PLoS ONEIdentifying mitosis is crucial for cancer diagnosis, but accurate detection remains difficult because of class imbalance and complex morphological variations in histopathological images.
Afnan M Alhassan, Nouf I Altmami
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Automated mitosis detection in stained histopathological images using Faster R-CNN and stain techniques [PDF]
Journal of Integrative BioinformaticsAccurate mitosis detection is essential for cancer diagnosis and treatment. Traditional manual counting by pathologists is time-consuming and may cause errors.
García-Salmerón Jesús +3 more
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A Two-Phase Mitosis Detection Approach Based on U-Shaped Network. [PDF]
Biomed Res Int, 2021 This paper proposes a deep learning‐based method for mitosis detection in breast histopathology images. A main problem in mitosis detection is that most of the datasets only have weak labels, i.e., only the coordinates indicating the center of the mitosis region.
Lu W.
europepmc +4 more sources
A multi-phase deep CNN based mitosis detection framework for breast cancer histopathological images [PDF]
Scientific Reports, 2021 The mitotic activity index is a key prognostic measure in tumour grading. Microscopy based detection of mitotic nuclei is a significant overhead and necessitates automation.
Anabia Sohail +4 more
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Mitosis detection using generic features and an ensemble of cascade adaboosts
Journal of Pathology Informatics, 2013 Context: Mitosis count is one of the factors that pathologists use to assess the risk of metastasis and survival of the patients, which are affected by the breast cancer. Aims: We investigate an application of a set of generic features and an ensemble of
F Boray Tek
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Journal of Pathology Informatics, 2013 Context: According to Nottingham grading system, mitosis count plays a critical role in cancer diagnosis and grading. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations.
Humayun Irshad
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Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach [PDF]
Journal of Pathology Informatics, 2013 Context: According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader
Humayun Irshad +6 more
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Cross-Scale Hypergraph Neural Networks with Inter–Intra Constraints for Mitosis Detection [PDF]
SensorsMitotic figures in tumor tissues are an important criterion for diagnosing malignant lesions, and physicians often search for the presence of mitosis in whole slide imaging (WSI).
Jincheng Li +6 more
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