AIMC Topic: Cell Nucleus

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Nucleus and cytoplasm-based segmentation and actor-critic neural network for acute lymphocytic leukaemia detection in single cell blood smear images.

Medical & biological engineering & computing Dec 6, 2019
Acute lymphoblastic leukaemia (ALL), which is due to the malfunctioning in the bone marrow, is common among people all over the world. The haematologist suffers a lot to discriminate the presence of leukaemia in the patients using the blood smears. T...
Entropy Fuzzy Logic Cell Nucleus Precursor Cell Lymphoblastic Leukemia-Lymphoma Algorithms Humans Reproducibility of Results Neural Networks, Computer Image Processing, Computer-Assisted
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Automated oral squamous cell carcinoma identification using shape, texture and color features of whole image strips.

Tissue & cell Dec 4, 2019
Despite profound knowledge of the incidence of oral cancers and a large body of research beyond it, it continues to beat diagnosis and treatment management. Post physical observation by clinicians, a biopsy is a gold standard for accurate detection o...
Image Processing, Computer-Assisted Datasets as Topic Biopsy Cell Nucleus Humans Female Mouth Neoplasms Artificial Intelligence Carcinoma, Squamous Cell Male
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DeepSynth: Three-dimensional nuclear segmentation of biological images using neural networks trained with synthetic data.

Scientific reports Dec 4, 2019
The scale of biological microscopy has increased dramatically over the past ten years, with the development of new modalities supporting collection of high-resolution fluorescence image volumes spanning hundreds of microns if not millimeters. The siz...
Rats Animals Cell Nucleus Deep Learning Imaging, Three-Dimensional Optical Imaging Image Processing, Computer-Assisted Kidney
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Robust blind spectral unmixing for fluorescence microscopy using unsupervised learning.

PloS one Dec 2, 2019
Due to the overlapping emission spectra of fluorophores, fluorescence microscopy images often have bleed-through problems, leading to a false positive detection. This problem is almost unavoidable when the samples are labeled with three or more fluor...
Microscopy, Confocal Unsupervised Machine Learning Photons Fluorescent Dyes Algorithms Actins Animals Endothelial Cells Microscopy, Fluorescence Fluorescence Pulmonary Artery Mitochondria Cattle Cell Nucleus
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A Multi-Organ Nucleus Segmentation Challenge.

IEEE transactions on medical imaging Oct 23, 2019
Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop and validate visual biomarkers for new digital pathology datasets. We summarize the results of MoNuSeg 2018 Challenge whose objective was to develop ge...
Cell Nucleus Humans Neural Networks, Computer Image Processing, Computer-Assisted
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Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images.

Medical image analysis Sep 18, 2019
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow. The development of automated methods for nuclear segmentation and classification enables th...
Neural Networks, Computer Colorectal Neoplasms Staining and Labeling Humans Histological Techniques Adenocarcinoma Datasets as Topic Cell Nucleus
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A segmentation method combining probability map and boundary based on multiple fully convolutional networks and repetitive training.

Physics in medicine and biology Sep 11, 2019
Cell nuclei image segmentation technology can help researchers observe each cell's stress response to drug treatment. However, it is still a challenge to accurately segment the adherent cell nuclei. At present, image segmentation based on a fully con...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Probability Cell Nucleus
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Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning.

Scientific reports Jul 19, 2019
Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. In this study, we demonstrate how deep learning framework can be used for an automatic classification of Renal Cell Carcinoma (R...
Carcinoma, Renal Cell Libraries, Digital Image Processing, Computer-Assisted Support Vector Machine Area Under Curve Cell Nucleus Kidney Tubules, Proximal Kidney Neoplasms Humans Deep Learning
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AMC-Net: Asymmetric and multi-scale convolutional neural network for multi-label HPA classification.

Computer methods and programs in biomedicine Jul 9, 2019
BACKGROUND AND OBJECTIVES: The multi-label Human Protein Atlas (HPA) classification can yield a better understanding of human diseases and help doctors to enhance the automatic analysis of biomedical images. The existing automatic protein recognition...
False Positive Reactions Pattern Recognition, Automated Cell Nucleus Proteins Databases, Protein Microscopy, Fluorescence Humans Phenotype Microscopy Reproducibility of Results Neural Networks, Computer Probability Algorithms Image Processing, Computer-Assisted Microtubules
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Multi-Path Dilated Residual Network for Nuclei Segmentation and Detection.

Cells May 23, 2019
As a typical biomedical detection task, nuclei detection has been widely used in human health management, disease diagnosis and other fields. However, the task of cell detection in microscopic images is still challenging because the nuclei are common...
Microscopy, Fluorescence Models, Biological Cell Nucleus Computer Storage Devices Eosine Yellowish-(YS) Hematoxylin Image Processing, Computer-Assisted Staining and Labeling Logistic Models Humans Deep Learning
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