scholarly journals QSM Reconstruction Challenge 2.0–Part 1: A Realistic in silico Head Phantom for MRI data simulation and evaluation of susceptibility mapping procedures

2020 ◽  
Author(s):  
José P. Marques ◽  
Jakob Meineke ◽  
Carlos Milovic ◽  
Berkin Bilgic ◽  
Kwok-Shing Chan ◽  
...  
Keyword(s):  
In Silico ◽  
Ground Truth ◽  
Susceptibility Mapping ◽  
Quantitative Mri ◽  
Reconstruction Algorithms ◽  
Imaging Data ◽  
Post Processing ◽  
Simulation Code ◽  
Wide Range ◽  
Echo Time

AbstractPurposeTo create a realistic in-silico head phantom for the second QSM Reconstruction Challenge and for future evaluations of processing algorithms for Quantitative Susceptibility Mapping (QSM).MethodsWe created a whole-head tissue property model by segmenting and post-processing high-resolution, multi-parametric MRI data acquired from a healthy volunteer. We simulated the steady-state magnetization using a Bloch simulator and mimicked a Cartesian sampling scheme through Fourier-based post-processing. We demonstrated some of the phantom’s properties, including the possibility of generating phase data that do not evolve linearly with echo time due to partial volume effects or complex distributions of frequency shifts within the voxel. Computer code for generating the phantom and performing the MR simulation was designed to facilitate flexible modifications of the model, such as the inclusion of pathologies, as well as the simulation of a wide range of acquisition protocols.ResultsThe brain-part of the phantom features realistic morphology combined with realistic spatial variations in relaxation and susceptibility values. Simulation code allows adjusting the following parameters and effects: repetition time and echo time, voxel size, background fields, and RF phase biases. Additionally, diffusion weighted imaging data of the phantom is provided allowing future investigations of tissue microstructure effects in phase and QSM algorithms.ConclusionThe presented phantom and computer programs are publicly available and may serve as a ground truth in future assessments of the faithfulness of quantitative MRI reconstruction algorithms.

scholarly journals Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

2019 ◽  
Author(s):  
Hesam Mazidi ◽  
Tianben Ding ◽  
Arye Nehorai ◽  
Matthew D. Lew
Keyword(s):  
Single Molecule ◽  
Computational Models ◽  
Amyloid Fibrils ◽  
Imaging System ◽  
Simulated Data ◽  
Super Resolution ◽  
Ground Truth ◽  
Localization Algorithm ◽  
Reconstruction Algorithms ◽  
Imaging Data

The resolution and accuracy of single-molecule localization micro-scopes (SMLMs) are routinely benchmarked using simulated data, calibration “rulers,” or comparisons to secondary imaging modalities. However, these methods cannot quantify the nanoscale accuracy of an arbitrary SMLM dataset. Here, we show that by computing localization stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly measure the confidence of individual localizations without ground-truth knowledge of the sample. We demonstrate that our method, termed Wasserstein-induced flux (WIF), measures the accuracy of various reconstruction algorithms directly on experimental 2D and 3D data of microtubules and amyloid fibrils. We further show that WIF confidences can be used to evaluate the mismatch between computational models and imaging data, enhance the accuracy and resolution of recon-structed structures, and discover hidden molecular heterogeneities. As a computational methodology, WIF is broadly applicable to any SMLM dataset, imaging system, and localization algorithm.

scholarly journals Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training

2020 ◽  
Author(s):  
Caroline Bivik Stadler ◽  
Martin Lindvall ◽  
Claes Lundström ◽  
Anna Bodén ◽  
Karin Lindman ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Image Data ◽  
Ground Truth ◽  
Lessons Learned ◽  
Training Data ◽  
Imaging Data ◽  
High Quality ◽  
High Quality Image ◽  
Specific Objective ◽  
Wide Range

Abstract Artificial intelligence (AI) holds much promise for enabling highly desired imaging diagnostics improvements. One of the most limiting bottlenecks for the development of useful clinical-grade AI models is the lack of training data. One aspect is the large amount of cases needed and another is the necessity of high-quality ground truth annotation. The aim of the project was to establish and describe the construction of a database with substantial amounts of detail-annotated oncology imaging data from pathology and radiology. A specific objective was to be proactive, that is, to support undefined subsequent AI training across a wide range of tasks, such as detection, quantification, segmentation, and classification, which puts particular focus on the quality and generality of the annotations. The main outcome of this project was the database as such, with a collection of labeled image data from breast, ovary, skin, colon, skeleton, and liver. In addition, this effort also served as an exploration of best practices for further scalability of high-quality image collections, and a main contribution of the study was generic lessons learned regarding how to successfully organize efforts to construct medical imaging databases for AI training, summarized as eight guiding principles covering team, process, and execution aspects.

scholarly journals Introduction to Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging

2019 ◽  
Vol 92 (1101) ◽  
pp. 20181016 ◽  
Author(s):  
Pascal P. R. Ruetten ◽  
Jonathan H. Gillard ◽  
Martin J. Graves
Keyword(s):  
Magnetic Field ◽  
Magnetic Susceptibility ◽  
External Magnetic Field ◽  
Clinical Applications ◽  
Susceptibility Mapping ◽  
Susceptibility Weighted Imaging ◽  
Post Processing ◽  
Quantitative Susceptibility Mapping ◽  
Wide Range

Quantitative Susceptibility Mapping (QSM) and Susceptibility Weighted Imaging (SWI) are MRI techniques that measure and display differences in the magnetization that is induced in tissues, i.e. their magnetic susceptibility, when placed in the strong external magnetic field of an MRI system. SWI produces images in which the contrast is heavily weighted by the intrinsic tissue magnetic susceptibility. It has been applied in a wide range of clinical applications. QSM is a further advancement of this technique that requires sophisticated post-processing in order to provide quantitative maps of tissue susceptibility. This review explains the steps involved in both SWI and QSM as well as describing some of their uses in both clinical and research applications.

scholarly journals Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Hesam Mazidi ◽  
Tianben Ding ◽  
Arye Nehorai ◽  
Matthew D. Lew
Keyword(s):  
Single Molecule ◽  
Computational Models ◽  
Amyloid Fibrils ◽  
Imaging System ◽  
Simulated Data ◽  
Super Resolution ◽  
Ground Truth ◽  
Localization Algorithm ◽  
Reconstruction Algorithms ◽  
Imaging Data

AbstractThe resolution and accuracy of single-molecule localization microscopes (SMLMs) are routinely benchmarked using simulated data, calibration rulers, or comparisons to secondary imaging modalities. However, these methods cannot quantify the nanoscale accuracy of an arbitrary SMLM dataset. Here, we show that by computing localization stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly measure the confidence of individual localizations without ground-truth knowledge of the sample. We demonstrate that our method, termed Wasserstein-induced flux (WIF), measures the accuracy of various reconstruction algorithms directly on experimental 2D and 3D data of microtubules and amyloid fibrils. We further show that WIF confidences can be used to evaluate the mismatch between computational models and imaging data, enhance the accuracy and resolution of reconstructed structures, and discover hidden molecular heterogeneities. As a computational methodology, WIF is broadly applicable to any SMLM dataset, imaging system, and localization algorithm.

scholarly journals Tracking calcium dynamics from individual neurons in behaving animals

2021 ◽  
Vol 17 (10) ◽  
pp. e1009432
Author(s):  
Thibault Lagache ◽  
Alison Hanson ◽  
Jesús E. Pérez-Ortega ◽  
Adrienne Fairhall ◽  
Rafael Yuste
Keyword(s):  
Visual Cortex ◽  
Calcium Imaging ◽  
Functional Characterization ◽  
Ground Truth ◽  
Time Lapse ◽  
Local Deformation ◽  
Neuron Activity ◽  
Imaging Data ◽  
Wide Range

Measuring the activity of neuronal populations with calcium imaging can capture emergent functional properties of neuronal circuits with single cell resolution. However, the motion of freely behaving animals, together with the intermittent detectability of calcium sensors, can hinder automatic monitoring of neuronal activity and their subsequent functional characterization. We report the development and open-source implementation of a multi-step cellular tracking algorithm (Elastic Motion Correction and Concatenation or EMC2) that compensates for the intermittent disappearance of moving neurons by integrating local deformation information from detectable neurons. We demonstrate the accuracy and versatility of our algorithm using calcium imaging data from two-photon volumetric microscopy in visual cortex of awake mice, and from confocal microscopy in behaving Hydra, which experiences major body deformation during its contractions. We quantify the performance of our algorithm using ground truth manual tracking of neurons, along with synthetic time-lapse sequences, covering a wide range of particle motions and detectability parameters. As a demonstration of the utility of the algorithm, we monitor for several days calcium activity of the same neurons in layer 2/3 of mouse visual cortex in vivo, finding significant turnover within the active neurons across days, with only few neurons that remained active across days. Also, combining automatic tracking of single neuron activity with statistical clustering, we characterize and map neuronal ensembles in behaving Hydra, finding three major non-overlapping ensembles of neurons (CB, RP1 and RP2) whose activity correlates with contractions and elongations. Our results show that the EMC2 algorithm can be used as a robust and versatile platform for neuronal tracking in behaving animals.

A Flying Gray Ball Multi-illuminant Image Dataset for Color Research

2020 ◽  
Vol 64 (5) ◽  
pp. 50411-1-50411-8
Author(s):  
Hoda Aghaei ◽  
Brian Funt
Keyword(s):  
Machine Vision ◽  
Spectral Reflectance ◽  
Color Constancy ◽  
Ground Truth ◽  
Practical Approach ◽  
Post Processing ◽  
Illumination Estimation ◽  
Processing Step ◽  
Image Dataset

Abstract For research in the field of illumination estimation and color constancy, there is a need for ground-truth measurement of the illumination color at many locations within multi-illuminant scenes. A practical approach to obtaining such ground-truth illumination data is presented here. The proposed method involves using a drone to carry a gray ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera. The captured images are then post-processed. In the post-processing step, machine vision techniques are used to detect the gray ball within each frame. The camera RGB of light reflected from the gray ball provides a measure of the illumination color at that location. In total, the dataset contains 30 scenes with 100 illumination measurements on average per scene. The dataset is available for download free of charge.

Comparative Study on Mitogen Activated Protein Kinase of Plasmodium Species by Using in silico Method

2012 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Mohd Fakharul Zaman Raja Yahya ◽  
Hasidah Mohd Sidek
Keyword(s):  
Amino Acid ◽  
In Silico ◽  
Nuclear Export ◽  
Nuclear Export Signal ◽  
Plasmodium Species ◽  
Mitogen Activated Protein Kinase ◽  
Multiple Sequence ◽  
Wide Range ◽  
Mitogen Activated Protein ◽  
Human Plasmodium

Malaria parasites, Plasmodium can infect a wide range of hosts including humans and rodents. There are two copies of mitogen activated protein kinases (MAPKs) in Plasmodium, namely MAPK1 and MAPK2. The MAPKs have been studied extensively in the human Plasmodium, P. falciparum. However, the MAPKs from other Plasmodium species have not been characterized and it is therefore the premise of presented study to characterize the MAPKs from other Plasmodium species-P. vivax, P. knowlesi, P. berghei, P. chabaudi and P.yoelli using a series of publicly available bioinformatic tools. In silico data indicates that all Plasmodium MAPKs are nuclear-localized and contain both a nuclear localization signal (NLS) and a Leucine-rich nuclear export signal (NES). The activation motifs of TDY and TSH were found to be fully conserved in Plasmodium MAPK1 and MAPK2, respectively. The detailed manual inspection of a multiple sequence alignment (MSA) construct revealed a total of 17 amino acid stack patterns comprising of different amino acids present in MAPKJ and MAPK2 respectively, with respect to rodent and human Plasmodia. It is proposed that these amino acid stack patterns may be useful in explaining the disparity between rodent and human Plasmodium MAPKs. 

Comparative Study on Mitogen Activated Protein Kinase of Plasmodium Species by Using In silico Method

2012 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Mohd Fakharul Zaman Raja Yahya ◽  
Hasidah Mohd Sidek
Keyword(s):  
Amino Acid ◽  
In Silico ◽  
Nuclear Export ◽  
Nuclear Export Signal ◽  
Plasmodium Species ◽  
Mitogen Activated Protein Kinase ◽  
Multiple Sequence ◽  
Bioinformatic Tools ◽  
Wide Range ◽  
Human Plasmodium

Malaria parasites, Plasmodium can infect a wide range ofhosts including humans and rodents. There are two copies ofmitogen activated protein kinases (MAPKs) in Plasmodium, namely MAPK1 and MAPK2. The MAPKs have been studied extensively in the human Plasmodium, P. falciparum. However, the MAPKs from other Plasmodium species have not been characterized and it is therefore the premise ofpresented study to characterize the MAPKs from other Plasmodium species-P. vivax, P. knowlesi, P. berghei, P. chabaudi and P.yoelli using a series ofpublicly available bioinformatic tools. In silico data indicates that all Plasmodium MAPKs are nuclear-localizedandcontain both a nuclear localization signal (NLS) anda Leucine-rich nuclear export signal (NES). The activation motifs ofTDYand TSH werefound to befully conserved in Plasmodium MAPK1 and MAPK2, respectively. The detailed manual inspection ofa multiple sequence alignment (MSA) construct revealed a total of 17 amino acid stack patterns comprising ofdifferent amino acids present in MAPK1 and MAPK2 respectively, with respect to rodent and human Plasmodia. 1t is proposed that these amino acid stack patterns may be useful in explaining the disparity between rodent and human Plasmodium MAPKs.

In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling

2019 ◽  
Vol 18 (26) ◽  
pp. 2209-2229 ◽  
Author(s):  
Hai Pham-The ◽  
Miguel Á. Cabrera-Pérez ◽  
Nguyen-Hai Nam ◽  
Juan A. Castillo-Garit ◽  
Bakhtiyor Rasulev ◽  
...  
Keyword(s):  
Intestinal Absorption ◽  
In Silico ◽  
Review Paper ◽  
Cell Monolayer ◽  
Cell Permeability ◽  
Drug Substances ◽  
Wide Range ◽  
Modeling Techniques

One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues.

Chalcones: As potent α-amylase enzyme inhibitors; synthesis, in vitro, and in silico studies

2020 ◽  
Vol 16 ◽  
Author(s):  
Mahboob Ali ◽  
Momin Khan ◽  
Khair Zaman ◽  
Abdul Wadood ◽  
Maryam Iqbal ◽  
...  
Keyword(s):  
In Silico ◽  
Enzyme Inhibitors ◽  
Biological Activities ◽  
Condensation Reaction ◽  
Type Ii Diabetes Mellitus ◽  
Spectroscopic Techniques ◽  
Chalcone Derivatives ◽  
In Silico Studies ◽  
Wide Range

: Background: The inhibition of α-amylase enzyme is one of the best therapeutic approach for the management of type II diabetes mellitus. Chalcone possesses a wide range of biological activities. Objective: In the current study chalcone derivatives (1-17) were synthesized and evaluated their inhibitory potential against α-amylase enzyme. Method: For that purpose, a library of substituted (E)-1-(naphthalene-2-yl)-3-phenylprop-2-en-1-ones was synthesized by ClaisenSchmidt condensation reaction of 2-acetonaphthanone and substituted aryl benzaldehyde in the presence of base and characterized via different spectroscopic techniques such as EI-MS, HREI-MS, 1H-, and 13C-NMR. Results: Sixteen synthetic chalcones were evaluated for in vitro porcine pancreatic α-amylase inhibition. All the chalcones demonstrated good inhibitory activities in the range of IC50 = 1.25 ± 1.05 to 2.40 ± 0.09 μM as compared to the standard commercial drug acarbose (IC50 = 1.34 ± 0.3 μM). Conclusion: Chalcone derivatives (1-17) were synthesized, characterized, and evaluated for their α-amylase inhibition. SAR revealed that electron donating groups in the phenyl ring have more influence on enzyme inhibition. However, to insight the participation of different substituents in the chalcones on the binding interactions with the α-amylase enzyme, in silico (computer simulation) molecular modeling analyses were carried out.

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