AIMC Topic: Cell Nucleus

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Fusion of encoder-decoder deep networks improves delineation of multiple nuclear phenotypes.

BMC bioinformatics Aug 7, 2018
BACKGROUND: Nuclear segmentation is an important step for profiling aberrant regions of histology sections. If nuclear segmentation can be resolved, then new biomarkers of nuclear phenotypes and their organization can be predicted for the application...
Humans Deep Learning Image Processing, Computer-Assisted Cell Nucleus Neural Networks, Computer Algorithms Phenotype
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Contour-Seed Pairs Learning-Based Framework for Simultaneously Detecting and Segmenting Various Overlapping Cells/Nuclei in Microscopy Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jul 18, 2018
In this paper, we propose a novel contour-seed pairs learning-based framework for robust and automated cell/nucleus segmentation. Automated granular object segmentation in microscopy images has significant clinical importance for pathology grading of...
Cervix Uteri Cell Line Microscopy Female Humans Cell Nucleus Animals Machine Learning Image Processing, Computer-Assisted Algorithms Drosophila
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RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation.

IEEE journal of biomedical and health informatics Jul 3, 2018
The level set based deformable models (LDM) are commonly used for medical image segmentation. However, they rely on a handcrafted curve evolution velocity that needs to be adapted for each segmentation task. The Convolutional Neural Networks (CNN) ad...
Image Interpretation, Computer-Assisted Humans Cell Nucleus Deep Learning Retina Heart Atria
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Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

BMC cancer May 30, 2018
BACKGROUND: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. Howev...
Cell Nucleus Receptors, Estrogen Breast Models, Biological Supervised Machine Learning Image Processing, Computer-Assisted Staining and Labeling Predictive Value of Tests Principal Component Analysis Neoplasm Staging Genetic Testing Breast Neoplasms Humans Middle Aged ROC Curve Aged Prognosis Young Adult Female Adult Risk Factors
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Development of a Robust Algorithm for Detection of Nuclei and Classification of White Blood Cells in Peripheral Blood Smear Images.

Journal of medical systems May 2, 2018
Peripheral Blood Smear analysis plays a vital role in diagnosis of many diseases such as leukemia, anemia, malaria, lymphoma and infections. Unusual variations in color, shape and size of blood cells indicate abnormal condition. We used a total of 11...
Humans Leukocytes Cell Nucleus Hematologic Tests Neural Networks, Computer Algorithms Image Processing, Computer-Assisted
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SetSVM: An Approach to Set Classification in Nuclei-Based Cancer Detection.

IEEE journal of biomedical and health informatics Feb 8, 2018
Due to the importance of nuclear structure in cancer diagnosis, several predictive models have been described for diagnosing a wide variety of cancers based on nuclear morphology. In many computer-aided diagnosis (CAD) systems, cancer detection tasks...
Cell Nucleus Microscopy Humans Databases, Factual Histocytochemistry Neoplasms Support Vector Machine Molecular Imaging Image Interpretation, Computer-Assisted
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Quantitative assessment of cancer cell morphology and motility using telecentric digital holographic microscopy and machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Dec 28, 2017
The noninvasive, fast acquisition of quantitative phase maps using digital holographic microscopy (DHM) allows tracking of rapid cellular motility on transparent substrates. On two-dimensional surfaces in vitro, MDA-MB-231 cancer cells assume several...
Microscopy, Fluorescence Cell Line, Tumor Cell Cycle Humans Cell Adhesion Machine Learning Cell Movement Cell Nucleus Neoplasm Invasiveness Holography Breast Neoplasms Actins
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Artificial neural network model to distinguish follicular adenoma from follicular carcinoma on fine needle aspiration of thyroid.

Diagnostic cytopathology Dec 20, 2017
BACKGROUND: To distinguish follicular adenoma (FA) and follicular carcinoma (FC) of thyroid in fine needle aspiration cytology (FNAC) is a challenging problem.
Thyroid Neoplasms Adenoma Diagnosis, Differential Humans Neural Networks, Computer Thyroid Gland Cell Nucleus Biopsy, Fine-Needle Adenocarcinoma, Follicular
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Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis.

Scientific reports Dec 20, 2017
Current cancer diagnosis employs various nuclear morphometric measures. While these have allowed accurate late-stage prognosis, early diagnosis is still a major challenge. Recent evidence highlights the importance of alterations in mechanical propert...
Humans Neural Networks, Computer Biomarkers, Tumor Image Interpretation, Computer-Assisted Neoplasms Cell Nucleus Deep Learning Optical Imaging Cell Line, Tumor
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Correlation Filters for Detection of Cellular Nuclei in Histopathology Images.

Journal of medical systems Nov 21, 2017
UNLABELLED: Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for ...
Humans Machine Learning Image Interpretation, Computer-Assisted Cell Nucleus Fourier Analysis
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