AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cytological Techniques

Showing 21 to 30 of 38 articles

Clear Filters

Generic Isolated Cell Image Generator.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Building automated cancer screening systems based on image analysis is currently a hot topic in computer vision and medical imaging community. One of the biggest challenges of such systems, especially those using state-of-the-art deep learning techni...

Training Convolutional Neural Networks and Compressed Sensing End-to-End for Microscopy Cell Detection.

IEEE transactions on medical imaging
Automated cell detection and localization from microscopy images are significant tasks in biomedical research and clinical practice. In this paper, we design a new cell detection and localization algorithm that combines deep convolutional neural netw...

Large-Scale Multi-Class Image-Based Cell Classification With Deep Learning.

IEEE journal of biomedical and health informatics
Recent advances in ultra-high-throughput microscopy have enabled a new generation of cell classification methodologies using image-based cell phenotypes alone. In contrast to current single-cell analysis techniques that rely solely on slow and costly...

GRUU-Net: Integrated convolutional and gated recurrent neural network for cell segmentation.

Medical image analysis
Cell segmentation in microscopy images is a common and challenging task. In recent years, deep neural networks achieved remarkable improvements in the field of computer vision. The dominant paradigm in segmentation is using convolutional neural netwo...

Cell Segmentation Using a Similarity Interface With a Multi-Task Convolutional Neural Network.

IEEE journal of biomedical and health informatics
Even though convolutional neural networks (CNN) have been used for cell segmentation, they require pixel-level ground truth annotations. This paper proposes a multitask learning algorithm for cell detection and segmentation using CNNs. We use dot ann...

Unsupervised Two-Path Neural Network for Cell Event Detection and Classification Using Spatiotemporal Patterns.

IEEE transactions on medical imaging
Automatic event detection in cell videos is essential for monitoring cell populations in biomedicine. Deep learning methods have advantages over traditional approaches for cell event detection due to their ability to capture more discriminative featu...

Evaluation of Machine Learning Classifiers to Predict Compound Mechanism of Action When Transferred across Distinct Cell Lines.

SLAS discovery : advancing life sciences R & D
Multiparametric high-content imaging assays have become established to classify cell phenotypes from functional genomic and small-molecule library screening assays. Several groups have implemented machine learning classifiers to predict the mechanism...

Nasal cytology with deep learning techniques.

International journal of medical informatics
BACKGROUND: In recent years, cytological observations in the Rhinology field are being increasingly utilized. This development has taken place over the last two decades and has proven to be fundamental in defining new nosological entities and in driv...

Cell Segmentation Based on FOPSO Combined With Shape Information Improved Intuitionistic FCM.

IEEE journal of biomedical and health informatics
Fuzzy c-means (FCM) clustering algorithms have been proved to be effective image segmentation techniques. However, FCM clustering algorithms are sensitive to noises and initialization. They cannot effectively segment cell images with inhomogeneous gr...