AIMC Topic: Mitosis

Clear Filters Showing 41 to 50 of 50 articles

An open-source solution for advanced imaging flow cytometry data analysis using machine learning.

Methods (San Diego, Calif.)
Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differe...

Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data.

PloS one
Medical diagnostics is often a multi-attribute problem, necessitating sophisticated tools for analyzing high-dimensional biomedical data. Mining this data often results in two crucial bottlenecks: 1) high dimensionality of features used to represent ...

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images.

IEEE transactions on medical imaging
The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases f...

Towards semantic-driven high-content image analysis: an operational instantiation for mitosis detection in digital histopathology.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study concerns a novel symbolic cognitive vision framework emerged from the Cognitive Microscopy (MICO(1)) initiative. MICO aims at supporting the evolution towards digital pathology, by studying cognitive clinical-compliant protocols involving ...

Classifying the AMi-Br Mitotic Figure Dataset with AUCMEDI.

Studies in health technology and informatics
INTRODUCTION: Mitotic figure (MF) density has been established as a key biomarker for certain tumors. Recently, the differentiation between atypical MFs (AMF) and normal MFs (NMFs) has gained increased interest in research, as AMFs density could be a...

De novo design and bioactivity prediction of mitotic kinesin Eg5 inhibitors using MPNN and LSTM-based transfer learning.

Computers in biology and medicine
Breast cancer, the most commonly diagnosed disease worldwide, has been linked to the overexpression of the kinesin Eg5 protein, a spindle motor protein crucial for the assembly and maintenance of the bipolar spindle during mitosis. This makes Eg5 an ...

Mitosis detection and classification for breast cancer diagnosis: What we know and what is next.

Computers in biology and medicine
Breast cancer is the second most deadly malignancy in women, behind lung cancer. Despite significant improvements in medical research, breast cancer is still accurately diagnosed with histological analysis. During this procedure, pathologists examine...

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 ...

Transfer learning based deep CNN for segmentation and detection of mitoses in breast cancer histopathological images.

Microscopy (Oxford, England)
Segmentation and detection of mitotic nuclei is a challenging task. To address this problem, a Transfer Learning based fast and accurate system is proposed. To give the classifier a balanced dataset, this work exploits the concept of Transfer Learnin...

Detection of mitotic nuclei in breast histopathology images using localized ACM and Random Kitchen Sink based classifier.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmen...