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Mitosis

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A Two-Phase Mitosis Detection Approach Based on U-Shaped Network.

BioMed research international
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 mi...

A deep learning approach for mitosis detection: Application in tumor proliferation prediction from whole slide images.

Artificial intelligence in medicine
The tumor proliferation, which is correlated with tumor grade, is a crucial biomarker indicative of breast cancer patients' prognosis. The most commonly used method in predicting tumor proliferation speed is the counting of mitotic figures in Hematox...

A multi-phase deep CNN based mitosis detection framework for breast cancer histopathological images.

Scientific reports
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. This work proposes deep CNN based multi-phase mitosis detection framework "M...

Grading of invasive breast carcinoma: the way forward.

Virchows Archiv : an international journal of pathology
Histologic grading has been a simple and inexpensive method to assess tumor behavior and prognosis of invasive breast cancer grading, thereby identifying patients at risk for adverse outcomes, who may be eligible for (neo)adjuvant therapies. Histolog...

Identification of Human Cell Cycle Phase Markers Based on Single-Cell RNA-Seq Data by Using Machine Learning Methods.

BioMed research international
The cell cycle is composed of a series of ordered, highly regulated processes through which a cell grows and duplicates its genome and eventually divides into two daughter cells. According to the complex changes in cell structure and biosynthesis, th...

Transformer-based unsupervised contrastive learning for histopathological image classification.

Medical image analysis
A large-scale and well-annotated dataset is a key factor for the success of deep learning in medical image analysis. However, assembling such large annotations is very challenging, especially for histopathological images with unique characteristics (...

pcnaDeep: a fast and robust single-cell tracking method using deep-learning mediated cell cycle profiling.

Bioinformatics (Oxford, England)
SUMMARY: Computational methods that track single cells and quantify fluorescent biosensors in time-lapse microscopy images have revolutionized our approach in studying the molecular control of cellular decisions. One barrier that limits the adoption ...

A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images.

Medical image analysis
Mitosis counting of biopsies is an important biomarker for breast cancer patients, which supports disease prognostication and treatment planning. Developing a robust mitotic cell detection model is highly challenging due to its complex growth pattern...

Multi CNN based automatic detection of mitotic nuclei in breast histopathological images.

Computers in biology and medicine
In breast cancer diagnosis, the number of mitotic cells in a specific area is an important measure. It indicates how far the tumour has spread, which has consequences for forecasting the aggressiveness of cancer. Mitosis counting is a time-consuming ...

Automatic detection of cell-cycle stages using recurrent neural networks.

PloS one
Mitosis is the process by which eukaryotic cells divide to produce two similar daughter cells with identical genetic material. Research into the process of mitosis is therefore of critical importance both for the basic understanding of cell biology a...