Differentiable optimization layers enhance GNN-based mitosis detection [PDF]
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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Mitosis detection using generic features and an ensemble of cascade adaboosts
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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Mitosis detection in histopathological images using customized deep learning and hybrid optimization algorithms. [PDF]
Identifying 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]
Accurate 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 multi-phase deep CNN based mitosis detection framework for breast cancer histopathological images [PDF]
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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A Subphase-Labeled Mitotic Dataset for AI-powered Cell Division Analysis [PDF]
Mitosis detection represents a critical task in digital pathology, as it plays an important role in the tumor grading and prognosis of patients. Manual determination is a labor-intensive task for practitioners with high interobserver variability, thus ...
Zsanett Zsofia Ivan +14 more
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Detection of mitotic tumor cells per tissue area is one of the critical markers of breast cancer prognosis. The aim of this paper is to develop a method for the automatic detection of mitotic figures from breast cancer histological slides using a ...
Meriem Sebai +2 more
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Adaptive example selection for prototype based explainable mitosis detection in digital pathology [PDF]
Understanding the decision-making process of black-box neural networks is crucial for safe use of AI in high-stakes medical tasks such as histopathology.
Mita Banik +4 more
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Toward interpretable and generalized mitosis detection in digital pathology using deep learning [PDF]
Objective The mitotic activity index is an important prognostic factor in the diagnosis of cancer. The task of mitosis detection is difficult as the nuclei are microscopic in size and partially labeled, and there are many more non-mitotic nuclei compared
Hasan Farooq +5 more
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Cross-Scale Hypergraph Neural Networks with Inter–Intra Constraints for Mitosis Detection [PDF]
Mitotic 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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