Fresnel incoherent correlation holographic localization microscopy with enhanced localization accuracy by employing autofocus algorithm

2021 ◽  
Author(s):  
Qin Zhang ◽  
Mengjing Jian ◽  
Chao Liu ◽  
Yuhong Wan
Keyword(s):  
Localization Accuracy ◽  
Localization Microscopy ◽  
Autofocus Algorithm

scholarly journals Artifact Formation in Single Molecule Localization Microscopy

2019 ◽  
Author(s):  
Jochen M. Reichel ◽  
Thomas Vomhof ◽  
Jens Michaelis
Keyword(s):  
Single Molecule ◽  
Ground Truth ◽  
Image Artifacts ◽  
Ground Truth Data ◽  
Localization Accuracy ◽  
Localization Microscopy ◽  
Trade Offs ◽  
Artifact Formation ◽  
Localization Behavior ◽  
Single Molecule Localization Microscopy

AbstractWe investigate the influence of different accuracy-detection rate trade-offs on image reconstruction in single molecule localization microscopy. Our main focus is the investigation of image artifacts experienced when using low localization accuracy, especially in the presence of sample drift and inhomogeneous background. In this context we present a newly developed SMLM software termed FIRESTORM which is optimized for high accuracy reconstruction. For our analysis we used in silico SMLM data and compared the reconstructed images to the ground truth data. We observe two discriminable reconstruction populations of which only one shows the desired localization behavior.

scholarly journals Single molecule localization microscopy with autonomous feedback loops for ultrahigh precision

2018 ◽  
Author(s):  
Simao Coelho ◽  
Jongho Baek ◽  
Matthew S. Graus ◽  
James M. Halstead ◽  
Philip R. Nicovich ◽  
...  
Keyword(s):  
Single Molecule ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Separation Distance ◽  
Distance Measurements ◽  
Intact Cells ◽  
Localization Accuracy ◽  
Localization Microscopy ◽  
Signaling Receptors ◽  
Single Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) promises to provide truly molecular scale images of biological specimens1–5. However, mechanical instabilities in the instrument, readout errors and sample drift constitute significant challenges and severely limit both the useable data acquisition length and the localization accuracy of single molecule emitters6. Here, we developed an actively stabilized total internal fluorescence (TIRF) microscope that performs 3D real-time drift corrections and achieves a stability of ≤1 nm. Self-alignment of the emission light path and corrections of readout errors of the camera automate channel alignment and ensure localization precisions of 1-4 nm in DNA origami structures and cells for different labels. We used Feedback SMLM to measure the separation distance of signaling receptors and phosphatases in T cells. Thus, an improved SMLM enables direct distance measurements between molecules in intact cells on the scale between 1-20 nm, potentially replacing Förster resonance energy transfer (FRET) to quantify molecular interactions7. In summary, by overcoming the major bottlenecks in SMLM imaging, it is possible to generate molecular images with nanometer accuracy and conduct distance measurements on the biological relevant length scales.

Role of pinnae and head movements in localizing pure tones 1The authors would like to thank Mr. Remi Humbert for implementing the experiment in Turbo Pascal and for his further assistance.

1999 ◽  
Vol 58 (3) ◽  
pp. 170-179 ◽  
Author(s):  
Barbara S. Muller ◽  
Pierre Bovet
Keyword(s):  
Sound Source ◽  
Head Movement ◽  
Movement Analysis ◽  
Head Movements ◽  
Sound Sources ◽  
Localization Accuracy ◽  
Sound Effects ◽  
Posterior Quadrant ◽  
Localization Performance ◽  
Pure Tones

Twelve blindfolded subjects localized two different pure tones, randomly played by eight sound sources in the horizontal plane. Either subjects could get information supplied by their pinnae (external ear) and their head movements or not. We found that pinnae, as well as head movements, had a marked influence on auditory localization performance with this type of sound. Effects of pinnae and head movements seemed to be additive; the absence of one or the other factor provoked the same loss of localization accuracy and even much the same error pattern. Head movement analysis showed that subjects turn their face towards the emitting sound source, except for sources exactly in the front or exactly in the rear, which are identified by turning the head to both sides. The head movement amplitude increased smoothly as the sound source moved from the anterior to the posterior quadrant.

Single-Molecule Imaging of Active Mitochondrial Nitroreductases using a Photo-Crosslinking Fluorescent Sensor

2019 ◽  
Author(s):  
Zacharias Thiel ◽  
Pablo Rivera-Fuentes
Keyword(s):  
Subcellular Localization ◽  
Fluorescent Probe ◽  
Single Molecule ◽  
Mammalian Cells ◽  
Fluorescent Sensor ◽  
Biological Functions ◽  
Localization Microscopy ◽  
Drug Activation ◽  
Nitroreductase Activity ◽  
Single Molecule Localization Microscopy

Many biomacromolecules are known to cluster in microdomains with specific subcellular localization. In the case of enzymes, this clustering greatly defines their biological functions. Nitroreductases are enzymes capable of reducing nitro groups to amines and play a role in detoxification and pro-drug activation. Although nitroreductase activity has been detected in mammalian cells, the subcellular localization of this activity remains incompletely characterized. Here, we report a fluorescent probe that enables super-resolved imaging of pools of nitroreductase activity within mitochondria. This probe is activated sequentially by nitroreductases and light to give a photo-crosslinked adduct of active enzymes. In combination with a general photoactivatable marker of mitochondria, we performed two-color, threedimensional, single-molecule localization microscopy. These experiments allowed us to image the sub-mitochondrial organization of microdomains of nitroreductase activity.<br>

Single-Molecule Imaging of Active Mitochondrial Nitroreductases using a Photo-Crosslinking Fluorescent Sensor

2019 ◽  
Author(s):  
Zacharias Thiel ◽  
Pablo Rivera-Fuentes
Keyword(s):  
Subcellular Localization ◽  
Fluorescent Probe ◽  
Single Molecule ◽  
Mammalian Cells ◽  
Fluorescent Sensor ◽  
Biological Functions ◽  
Localization Microscopy ◽  
Drug Activation ◽  
Nitroreductase Activity ◽  
Single Molecule Localization Microscopy

Many biomacromolecules are known to cluster in microdomains with specific subcellular localization. In the case of enzymes, this clustering greatly defines their biological functions. Nitroreductases are enzymes capable of reducing nitro groups to amines and play a role in detoxification and pro-drug activation. Although nitroreductase activity has been detected in mammalian cells, the subcellular localization of this activity remains incompletely characterized. Here, we report a fluorescent probe that enables super-resolved imaging of pools of nitroreductase activity within mitochondria. This probe is activated sequentially by nitroreductases and light to give a photo-crosslinked adduct of active enzymes. In combination with a general photoactivatable marker of mitochondria, we performed two-color, threedimensional, single-molecule localization microscopy. These experiments allowed us to image the sub-mitochondrial organization of microdomains of nitroreductase activity.<br>

Weighted Minimum Entropy Autofocus Algorithm for ISAR Imaging

2011 ◽  
Vol 33 (8) ◽  
pp. 1809-1815
Author(s):  
Gang Xu ◽  
Lei Yang ◽  
Lei Zhang ◽  
Ya-chao Li ◽  
Meng-dao Xing
Keyword(s):  
Minimum Entropy ◽  
Isar Imaging ◽  
Autofocus Algorithm

A Comparative Study of Computational Intelligence Algorithms for Sensor Localization

2019 ◽  
Vol 9 (2) ◽  
pp. 224-236
Author(s):  
Vaishali R. Kulkarni ◽  
Veena Desai ◽  
Raghavendra Kulkarni
Keyword(s):  
Firefly Algorithm ◽  
Heuristic Algorithms ◽  
Computing Time ◽  
Sensor Nodes ◽  
Convergence Time ◽  
Localization Error ◽  
Location Awareness ◽  
Cultural Algorithm ◽  
Localization Accuracy ◽  
Multi Stage

Background & Objective: Location of sensors is an important information in wireless sensor networks for monitoring, tracking and surveillance applications. The accurate and quick estimation of the location of sensor nodes plays an important role. Localization refers to creating location awareness for as many sensor nodes as possible. Multi-stage localization of sensor nodes using bio-inspired, heuristic algorithms is the central theme of this paper. Methodology: Biologically inspired heuristic algorithms offer the advantages of simplicity, resourceefficiency and speed. Four such algorithms have been evaluated in this paper for distributed localization of sensor nodes. Two evolutionary computation-based algorithms, namely cultural algorithm and the genetic algorithm, have been presented to optimize the localization process for minimizing the localization error. The results of these algorithms have been compared with those of swarm intelligence- based optimization algorithms, namely the firefly algorithm and the bee algorithm. Simulation results and analysis of stage-wise localization in terms of number of localized nodes, computing time and accuracy have been presented. The tradeoff between localization accuracy and speed has been investigated. Results: The comparative analysis shows that the firefly algorithm performs the localization in the most accurate manner but takes longest convergence time. Conclusion: Further, the cultural algorithm performs the localization in a very quick time; but, results in high localization error.

scholarly journals Imitation learning-based framework for learning 6-D linear compliant motions

2021 ◽  
Author(s):  
Markku Suomalainen ◽  
Fares J. Abu-dakka ◽  
Ville Kyrki
Keyword(s):  
Contact Force ◽  
Free Space ◽  
Prior Information ◽  
Goal Area ◽  
Imitation Learning ◽  
Learning From Demonstration ◽  
End Effector ◽  
Localization Accuracy ◽  
Novel Method ◽  
Contact Tasks

AbstractWe present a novel method for learning from demonstration 6-D tasks that can be modeled as a sequence of linear motions and compliances. The focus of this paper is the learning of a single linear primitive, many of which can be sequenced to perform more complex tasks. The presented method learns from demonstrations how to take advantage of mechanical gradients in in-contact tasks, such as assembly, both for translations and rotations, without any prior information. The method assumes there exists a desired linear direction in 6-D which, if followed by the manipulator, leads the robot’s end-effector to the goal area shown in the demonstration, either in free space or by leveraging contact through compliance. First, demonstrations are gathered where the teacher explicitly shows the robot how the mechanical gradients can be used as guidance towards the goal. From the demonstrations, a set of directions is computed which would result in the observed motion at each timestep during a demonstration of a single primitive. By observing which direction is included in all these sets, we find a single desired direction which can reproduce the demonstrated motion. Finding the number of compliant axes and their directions in both rotation and translation is based on the assumption that in the presence of a desired direction of motion, all other observed motion is caused by the contact force of the environment, signalling the need for compliance. We evaluate the method on a KUKA LWR4+ robot with test setups imitating typical tasks where a human would use compliance to cope with positional uncertainty. Results show that the method can successfully learn and reproduce compliant motions by taking advantage of the geometry of the task, therefore reducing the need for localization accuracy.

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