Data fusion and smoothing for probabilistic tracking of viral structures in fluorescence microscopy images

Ritter, Christian; Wollmann, Thomas; Lee, Ji Young; Imle, Andrea; Müller, Bárbara; Fackler, Oliver T.; Bartenschlager, Ralf; Rohr, Karl

doi:10.1016/j.media.2021.102168

Cited by 17 publications

(11 citation statements)

References 35 publications

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“…Features based on [11] use the keypoint movements to identify temporal patterns like directed or undirected motion.…”

Section: Methodsmentioning

confidence: 99%

DeepRod: A human-in-the-loop system for automatic rodent behavior analysis

Loy,

Garafolj,

Schauerte

et al. 2024

Preprint

Self Cite

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We present a human-in-the-loop system for efficient rodent behavior analysis in drug development. Addressing the time-consuming and labor-intensive nature of manual behavior categorization, this UX-optimized platform integrates AI for complex behavior prediction and active learning to identify rare events. The proposed solution leverages a cloud-native data processing pipeline, AI-based novelty behavior recognition and multi-class classification, demonstrating significant improvements in behavior labeling and discovery.

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“…Features based on [11] use the keypoint movements to identify temporal patterns like directed or undirected motion.…”

Section: Methodsmentioning

confidence: 99%

DeepRod: A human-in-the-loop system for automatic rodent behavior analysis

Loy,

Garafolj,

Schauerte

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

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“…However, tracking these movements was laborious and challenging due to the large number of small vesicles, their low signal to noise ratio compared to the much brighter Golgi and their dispersed origins from Golgi mini-stacks throughout the cytoplasm (Figure 3A). Many different tracking algorithms have been developed in recent years that use deep learning (DL) methods to enhance target detection and object tracking [17][18][19][20][21][22][23][24][25][26][27][30][31][32]. However, these machine learning methods usually require an extensive training dataset that must be updated for each new experimental system, which can be impractical and time consuming, some were developed for particular imaging techniques, while others perform poorly in a noisy environment.…”

Section: The Msp-tracker and Msp-viewer Programsmentioning

confidence: 99%

“…Many different tracking algorithms have been developed in recent years [17][18][19][20][21][22][23][24][25] .…”

Section: Introductionmentioning

confidence: 99%

Tracking exocytic vesicle movements reveals the spatial control of secretion in epithelial cells

Richens,

Dmitrieva,

Zenner

et al. 2024

Preprint

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Understanding how specific secretory cargoes are targeted to distinct domains of the plasma membrane in epithelial cells requires analysing the trafficking of post-Golgi vesicles to their sites of secretion. Here, we introduce an interactive vesicle tracking framework, the multiscale particle tracker and viewer, that exploits developments in computer vision and deep learning to determine vesicle trajectories in noisy cellular environments without the need for extensive training data. We analysed the movements of secreted cargoes in the Drosophila follicular epithelium ex vivo with high temporal and spatial resolution and found that MSP-tracker outperformed other tracking software. Using the RUSH (retention using selective hooks) system to synchronously release cargoes from the endoplasmic reticulum, we followed the movements the microvillar protein, Cadherin 99C, to the plasma membrane. A dominant slow dynein mutant reduces the speed of apical Cad99C movements, demonstrating that dynein transports Cad99C vesicles to the apical cortex. Furthermore, both the dynein mutant and microtubule depolymerisation cause lateral Cad99C secretion. Thus, microtubule organisation plays a central role in targeting secretion, suggesting that Drosophila does not have distinct apical versus basolateral vesicle fusion machinery. Imaging the extracellular matrix protein (ECM) proteins, Nidogen and Collagen IV revealed that Nidogen vesicles undergo planar-polarised transport to the leading edge of follicle cells as they migrate over the ECM, whereas most Collagen is secreted at trailing edges. The follicle cells therefore secrete different ECM components at opposite sides of the cell, revealing that the secretory pathway is more spatially organised than previously thought.

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“…Afterwards, the intersection of all nearest neighbor queries is computed, which determines triple colocalizations within all three channels. Due to the data structure of k-d-trees, the nearest neighbor queries have an average running time of O(log(n)), where n is the number of particles in a channel [29], [31], [32]. Thus, this data structure is efficient, easy to construct, and well suited for finding nearest neighbors to determine triple colocalizations.…”

Section: A Quantification Of Colocalization Using Colocquantmentioning

confidence: 99%

Multi-Channel Colocalization Analysis and Visualization of Viral Proteins in Fluorescence Microscopy Images

et al. 2023

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Automatic analysis of colocalizing biological structures in multi-channel fluorescence microscopy images is an important task to quantify and understand biological processes at high spatialtemporal resolution. Here, we introduce a software suite for colocalization analysis of spot-like objects in multi-channel fluorescence microscopy images. The software suite consists of ColocQuant and ColocJ, and is easy to use for biologists. ColocQuant is a Python-based software with graphical user interface to quantify colocalization of particles in two or three channels. Object-based colocalization is performed by an efficient multi-dimensional graph-based k-d-tree approach, which determines nearest neighbors involved in double or triple colocalization. ColocJ enables efficient and intuitive visualization of the color composition of colocalizations by a Maxwell color triangle and a color ribbon. Colocalization information can be visualized for an entire image or a selected region-of-interest. In addition, global statistics of the particle intensity, particle size, and the number of colocalizations over time are provided. The colocalization analysis results can be exported and used in other software. We illustrate the application of our software suite for multichannel live cell fluorescence microscopy image sequences of viral proteins in hepatitis C virus infected cells. We performed two-channel and three-channel colocalization analysis.INDEX TERMS Biomedical imaging, microscopy images, colocalization analysis, viral proteins.

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Data fusion and smoothing for probabilistic tracking of viral structures in fluorescence microscopy images

Cited by 17 publications

References 35 publications

DeepRod: A human-in-the-loop system for automatic rodent behavior analysis

DeepRod: A human-in-the-loop system for automatic rodent behavior analysis

Tracking exocytic vesicle movements reveals the spatial control of secretion in epithelial cells

Multi-Channel Colocalization Analysis and Visualization of Viral Proteins in Fluorescence Microscopy Images

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