scholarly journals Robust and automated motion correction for real infant fNIRS data

2020 ◽  
Author(s):  
Lindsey J Powell
Keyword(s):  
Motion Correction ◽  
Hemodynamic Response ◽  
Motion Artifacts ◽  
Response Functions ◽  
Correction Procedure ◽  
Response Signal ◽  
Hemodynamic Responses ◽  
Differential Responses ◽  
Difficult Challenge

Although many approaches have been proposed, removing motion artifacts from developmental fNIRS data remains a difficult challenge. In particular, the lack of consistency in motion correction approaches across experimental reports suggests that the field has not yet identified an algorithm that consistently removes the majority of motion contamination while retaining hemodynamic responses, regardless of the idiosyncrasies of particular datasets. Some existing approaches remove the same fraction of variance from each participant’s data; others use participant data to set filtering parameters in ways that result in more stringent thresholds for low-motion participants than high-motion participants. Both types of approach risk leaving artifacts in data from participants with the most motion, while removing signal from participants with the least motion. In contrast, the procedure proposed here identifies and filters motion artifacts on the basis of a fixed, physiologically-justified threshold, so that amount of variance removed is closely associated with the prevalence of motion in each participant’s data. Across multiple contrasts from real experimental datasets, this procedure effectively removes motion artifacts while retaining the hemodynamic response signal, allowing the detection of differential responses to conditions, and recovering canonical hemodynamic response functions for both oxygenated and deoxygenated timecourses, indicated by robust negative correlations between the two hemoglobin types. This motion correction procedure would be appropriate to preregister as a planned component of the preprocessing stream in future fNIRS research.

scholarly journals Motion correction for routine X-ray lung CT imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Doil Kim ◽  
Jiyoung Choi ◽  
Duhgoon Lee ◽  
Hyesun Kim ◽  
Jiyoung Jung ◽  
...  
Keyword(s):  
Motion Estimation ◽  
Motion Correction ◽  
Ct Imaging ◽  
Motion Artifacts ◽  
Ct Scans ◽  
Breath Hold ◽  
X Ray ◽  
Wide Range ◽  
Thorax Ct ◽  
Lung Ct

AbstractA novel motion correction algorithm for X-ray lung CT imaging has been developed recently. It was designed to perform for routine chest or thorax CT scans without gating, namely axial or helical scans with pitch around 1.0. The algorithm makes use of two conjugate partial angle reconstruction images for motion estimation via non-rigid registration which is followed by a motion compensated reconstruction. Differently from other conventional approaches, no segmentation is adopted in motion estimation. This makes motion estimation of various fine lung structures possible. The aim of this study is to explore the performance of the proposed method in correcting the lung motion artifacts which arise even under routine CT scans with breath-hold. The artifacts are known to mimic various lung diseases, so it is of great interest to address the problem. For that purpose, a moving phantom experiment and clinical study (seven cases) were conducted. We selected the entropy and positivity as figure of merits to compare the reconstructed images before and after the motion correction. Results of both phantom and clinical studies showed a statistically significant improvement by the proposed method, namely up to 53.6% (p < 0.05) and up to 35.5% (p < 0.05) improvement by means of the positivity measure, respectively. Images of the proposed method show significantly reduced motion artifacts of various lung structures such as lung parenchyma, pulmonary vessels, and airways which are prominent in FBP images. Results of two exemplary cases also showed great potential of the proposed method in correcting motion artifacts of the aorta which is known to mimic aortic dissection. Compared to other approaches, the proposed method provides an excellent performance and a fully automatic workflow. In addition, it has a great potential to handle motions in wide range of organs such as lung structures and the aorta. We expect that this would pave a way toward innovations in chest and thorax CT imaging.

scholarly journals Characterization of the hemodynamic response of the hippocampal and parahippocampal regions using FMRI

2021 ◽  
Author(s):  
Priyanka Mehta
Keyword(s):  
Spatial Memory ◽  
Medial Temporal Lobe ◽  
Dominant Role ◽  
Memory Task ◽  
Hemodynamic Response ◽  
Hemodynamic Responses ◽  
Memory Processing ◽  
Time To Peak ◽  
Hemodynamic Characteristics ◽  
The Right

Previous neuroimaging studies have suggested a dominant role of the right medial temporal lobe (MTL) structures- the hippocampal and parahippocampal regions in spatial memory processing. However, the underlying physiological hemodynamic response functions (HRF) of the MTL substructures remain undefined. Given the neuroanatomical differences between these substructures, it is posited that their hemodynamic characteristics are distinct. In this study, the hemodynamic responses of the MTL substructures are investigated using an optimization algorithm that penalizes the curvature (i.e. second derivative) of HRF. The time-to-peak characteristic of the hemodynamic responses revealed that the right CA3 and DG subfields of the hippocampus are significantly more active than the right CA1 subfield during a specific spatial memory task. Further, the hemodynamic responses of the entorhinal, perirhinal and parahippocampal cortices are presented. Together, these findings may help advance our understanding of neurodegenerative diseases like epilepsy and Alzheimer’s disease that are strongly associated to hippocampal dysfunction.

Detecting task-dependent functional connectivity in GIMME with person-specific hemodynamic response functions

2021 ◽  
Author(s):  
Kelly Anne Duffy ◽  
Zachary F. Fisher ◽  
Cara A. Arizmendi ◽  
Peter C.M. Molenaar ◽  
Joseph Hopfinger ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Hemodynamic Response ◽  
Response Functions

Motion artifacts in endoscopic catheter-based images: simulation and motion correction method

2018 ◽  
Author(s):  
Elham Abouei ◽  
Anthony M. Lee ◽  
Pierre Lane ◽  
Calum MacAulayb ◽  
Stephen Lam ◽  
...  
Keyword(s):  
Motion Correction ◽  
Correction Method ◽  
Motion Artifacts ◽  
Motion Correction Method

scholarly journals A Motion Correction Framework for Time Series Sequences in Microscopy Images

2013 ◽  
Vol 19 (2) ◽  
pp. 433-450 ◽  
Author(s):  
Ankur N. Kumar ◽  
Kurt W. Short ◽  
David W. Piston
Keyword(s):  
Time Series ◽  
Blood Flow ◽  
Motion Correction ◽  
Laser Scanning ◽  
Flow Analysis ◽  
Three Dimensional ◽  
Motion Artifacts ◽  
Microscopy Techniques ◽  
Microscopy Images

AbstractWith the advent of in vivo laser scanning fluorescence microscopy techniques, time-series and three-dimensional volumes of living tissue and vessels at micron scales can be acquired to firmly analyze vessel architecture and blood flow. Analysis of a large number of image stacks to extract architecture and track blood flow manually is cumbersome and prone to observer bias. Thus, an automated framework to accomplish these analytical tasks is imperative. The first initiative toward such a framework is to compensate for motion artifacts manifest in these microscopy images. Motion artifacts in in vivo microscopy images are caused by respiratory motion, heart beats, and other motions from the specimen. Consequently, the amount of motion present in these images can be large and hinders further analysis of these images. In this article, an algorithmic framework for the correction of time-series images is presented. The automated algorithm is comprised of a rigid and a nonrigid registration step based on shape contexts. The framework performs considerably well on time-series image sequences of the islets of Langerhans and provides for the pivotal step of motion correction in the further automatic analysis of microscopy images.

Plasma Concentration of Fentanyl with Xenon to Block Somatic and Hemodynamic Responses to Surgical Incision

2000 ◽  
Vol 92 (4) ◽  
pp. 1043-1048 ◽  
Author(s):  
Yoshinori Nakata ◽  
Takahisa Goto ◽  
Hayato Saito ◽  
Yoshiki Ishiguro ◽  
Katsuo Terui ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Plasma Concentrations ◽  
Hemodynamic Response ◽  
Skin Incision ◽  
Computer Assisted ◽  
Hemodynamic Responses ◽  
Surgical Incision ◽  
Model Driven ◽  
Bodily Movement ◽  
Somatic Response

Background Although anesthesia with xenon has been supplemented with fentanyl, its requirement has not been established. This study was conducted to determine the plasma concentrations of fentanyl necessary to suppress somatic and hemodynamic responses to surgical incision in 50% patients in the presence of 0.7 minimum alveolar concentration (MAC) xenon. Methods Twenty-five patients were allocated randomly to predetermined fentanyl concentration between 0.5 and 4.0 ng/ml during 0.7 MAC xenon anesthesia. Fentanyl was administered using a pharmacokinetic model-driven computer-assisted continuous infusion device. At surgical incision each patient was monitored for somatic and hemodynamic responses. A somatic response was defined as any purposeful bodily movement. A positive hemodynamic response was defined as a more than 15% increase in heart rate or mean arterial pressure more than the preincision value. The concentrations of fentanyl to prevent somatic and hemodynamic responses in 50% of patients were calculated using logistic regression. Results The concentration of fentanyl to prevent a somatic response to skin incision in 50% of patients in the presence of 0.7 MAC xenon was 0.72 +/- 0.07 ng/ml and to prevent a hemodynamic response was 0.94 +/- 0.06 ng/ml. Conclusions Comparing these results with previously published results in the presence of 70% nitrous oxide, the fentanyl requirement in xenon anesthesia is smaller than that in the equianesthetic nitrous oxide anesthesia.

scholarly journals An investigation of positive and inverted hemodynamic response functions across multiple visual areas

2014 ◽  
Vol 35 (11) ◽  
pp. 5550-5564 ◽  
Author(s):  
Alexander M. Puckett ◽  
Jedidiah R. Mathis ◽  
Edgar A. DeYoe
Keyword(s):  
Hemodynamic Response ◽  
Response Functions ◽  
Visual Areas

scholarly journals NoRMCorre: An online algorithm for piecewise rigid motion correction of calcium imaging data

2017 ◽  
Author(s):  
Eftychios A. Pnevmatikakis ◽  
Andrea Giovannucci
Keyword(s):  
Calcium Imaging ◽  
Motion Correction ◽  
Rigid Motion ◽  
Motion Artifacts ◽  
Streaming Data ◽  
Field Of View ◽  
Large Field ◽  
Motion Field ◽  
Imaging Data ◽  
Two Photon

AbstractBackgroundMotion correction is a challenging pre-processing problem that arises early in the analysis pipeline of calcium imaging data sequences. The motion artifacts in two-photon microscopy recordings can be non-rigid, arising from the finite time of raster scanning and non-uniform deformations of the brain medium.New methodWe introduce an algorithm for fast Non-Rigid Motion Correction (NoRMCorre) based on template matching. NoRMCorre operates by splitting the field of view into overlapping spatial patches that are registered at a sub-pixel resolution for rigid translation against a continuously updated template. The estimated alignments are subsequently up-sampled to create a smooth motion field for each frame that can efficiently approximate non-rigid motion in a piecewise-rigid manner.Existing methodsExisting approaches either do not scale well in terms of computational performance or are targeted to motion artifacts arising from low speed scanning, whereas modern datasets with large field of view are more prone to non-rigid brain deformation issues.ResultsNoRMCorre can be run in an online mode resulting in comparable to or even faster than real time motion registration on streaming data. We evaluate the performance of the proposed method with simple yet intuitive metrics and compare against other non-rigid registration methods on two-photon calcium imaging datasets. Open source Matlab and Python code is also made available.ConclusionsThe proposed method and code provide valuable support to the community for solving large scale image registration problems in calcium imaging, especially when non-rigid deformations are present in the acquired data.

scholarly journals Attenuation of Motion Artifacts in fMRI using Discrete Reconstruction of Irregular fMRI Trajectories (DRIFT)

2019 ◽  
Author(s):  
David Parker ◽  
Qolamreza Razlighi
Keyword(s):  
Motion Correction ◽  
Pulse Sequence ◽  
Hybrid Approach ◽  
Simulated Data ◽  
Bloch Equation ◽  
Motion Artifacts ◽  
Fmri Data ◽  
Out Of Plane ◽  
Motion Problem ◽  
Processing Techniques

AbstractNumerous studies reported motion as the most detrimental source of noise and artifacts in functional magnetic resonance imaging (fMRI). Different approaches have been proposed and used to attenuate the effect of motion on fMRI data, including both prospective and retrospective (post-processing) techniques. However, each type of motion (e.g. translation versus rotation or in-plane versus out-of-plane) has a distinct effect on the MR signal, which is not fully understood nor appropriately modeled in the field. In addition, effects of the same motion can be substantially different depending on when it occurs during the pulse sequence (e.g. RF excitation, gradient encoding, or k-space read-out). Thus, each distinct kind of motion and the time of its occurrence may require a unique approach to be optimally corrected. Therefore, we start with an investigation of the effects of different motions on the MR signal based on the Bloch equation. We then simulate their unique effects with a comprehensive fMRI simulator. Our results indicate that current motion correction methods fail to completely address the motion problem. Retrospective techniques such as spatial realignment can correct for between-volume misalignment, but fail to address within volume contamination and spin-history artifacts. Because of the steady state nature of the fMRI acquisition, spin-history artifacts arising from over/under excitation during slice-selection causes the motion artifacts to contaminate MR signal even after cessation of motion, which makes it challenging to be corrected retrospectively. Prospective motion correction has been proposed to prevent spin-history artifacts, but fails to address motion artifacts during k-space readout. In this article, we propose a novel method to remove these artifacts: Discrete reconstruction of irregular fMRI trajectory (DRIFT). Our method calculates the exact displacement of k-space recording due to motion at each dwell time and retrospectively corrects each slice of the fMRI volume using an inverse nonuniform Fourier transform. We evaluate our proposed methods using simulated data as well as fMRI data collected from a rotating phantom inside a 3T Siemens Prisma scanner. We conclude that a hybrid approach with both prospective and retrospective components are essentially required for optimal removal of motion artifacts from the fMRI data.

Sign in / Sign up

Export Citation Format

Share Document