Mitosis detection using generic features and an ensemble of cascade adaboosts [PDF]
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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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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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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Cell mitosis detection using deep neural networks [PDF]
Knowledge-Based Systems, 2017 Quantitative analysis of cell mitosis, the process by which cells regenerate, is important in cell biology. Automatic cell mitosis detection can greatly facilitate the investigation of cell life cycle. However, cell-type diversity, cell non-rigid deformation and high cell density pose difficulties on handcrafting visual features for traditional ...
Zhang Yi, Yao Zhou
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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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Recent Advances in Automated Mitosis Detection in Digital Pathology: A PRISMA-Guided Systematic Review with Evaluation-Regime Stratification (2018–2025) [PDF]
BiomedicinesBackground/Objectives: Recent advances in automated mitosis detection in H&E histopathology have expanded AI applications in digital pathology for tumor grading and proliferation assessment.
Mohamed Albahri +5 more
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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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Adaptive example selection for prototype based explainable mitosis detection in digital pathology [PDF]
Scientific ReportsUnderstanding 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]
Digital HealthObjective 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]
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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