Deep learning for cellular image analysis
Recent advances in computer vision and machine learning underpin a collection of
algorithms with an impressive ability to decipher the content of images. These deep learning …
algorithms with an impressive ability to decipher the content of images. These deep learning …
A survey on applications of deep learning in microscopy image analysis
Z Liu, L Jin, J Chen, Q Fang, S Ablameyko, Z Yin… - Computers in biology …, 2021 - Elsevier
Advanced microscopy enables us to acquire quantities of time-lapse images to visualize the
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
A learning Gaussian process approach for maneuvering target tracking and smoothing
W Aftab, L Mihaylova - IEEE Transactions on Aerospace and …, 2020 - ieeexplore.ieee.org
Model-based approaches for target tracking and smoothing estimate the infinite number of
possible target trajectories using a finite set of models. This article proposes a data-driven …
possible target trajectories using a finite set of models. This article proposes a data-driven …
Multi-sensor multi-target tracking using domain knowledge and clustering
This paper proposes a novel joint multi-target tracking and track maintenance algorithm over
a sensor network. Each sensor runs a local joint probabilistic data association (JPDA) filter …
a sensor network. Each sensor runs a local joint probabilistic data association (JPDA) filter …
Yeastnet: Deep-learning-enabled accurate segmentation of budding yeast cells in bright-field microscopy
Accurate and efficient segmentation of live-cell images is critical in maximizing data
extraction and knowledge generation from high-throughput biology experiments. Despite …
extraction and knowledge generation from high-throughput biology experiments. Despite …
Toward Real-Time Animal Tracking with Integrated Stimulus Control for Automated Conditioning in Aquatic Eco-Neurotoxicology
Aquatic eco-neurotoxicology is an emerging field that requires new analytical systems to
study the effects of pollutants on animal behaviors. This is especially true if we are to gain …
study the effects of pollutants on animal behaviors. This is especially true if we are to gain …
A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos
We present a novel computational framework for the analysis of high-throughput microscopy
videos of living cells. The proposed framework is generally useful and can be applied to …
videos of living cells. The proposed framework is generally useful and can be applied to …
A discrete chain graph model for 3d+ t cell tracking with high misdetection robustness
Tracking by assignment is well suited for tracking a varying number of divisible cells, but
suffers from false positive detections. We reformulate tracking by assignment as a chain …
suffers from false positive detections. We reformulate tracking by assignment as a chain …
Cell morphology classification and clutter mitigation in phase-contrast microscopy images using machine learning
We propose using machine learning techniques to analyze the shape of living cells in phase-
contrast microscopy images. Large scale studies of cell shape are needed to understand the …
contrast microscopy images. Large scale studies of cell shape are needed to understand the …
Tracking of cell populations to understand their spatio-temporal behavior in response to physical stimuli
D House, ML Walker, Z Wu, JY Wong… - 2009 IEEE Computer …, 2009 - ieeexplore.ieee.org
We have developed methods for segmentation and tracking of cells in time-lapse phase-
contrast microscopy images. Our multi-object Bayesian algorithm detects and tracks large …
contrast microscopy images. Our multi-object Bayesian algorithm detects and tracks large …