scholarly journals Automated Midline Estimation for Symmetry Analysis of Cerebral Hemispheres in FLAIR MRI

2021 ◽  
Vol 13 ◽  
Author(s):  
Adam Gibicar ◽  
Alan R. Moody ◽  
April Khademi
Keyword(s):  
Sagittal Plane ◽  
Control Point ◽  
Asymmetry Index ◽  
Point Estimation ◽  
Cerebral Hemispheres ◽  
Absolute Difference ◽  
Natural Phenomenon ◽  
Average Error ◽  
Texture Gradient ◽  
Angle Correction

To perform brain asymmetry studies in large neuroimaging archives, reliable and automatic detection of the interhemispheric fissure (IF) is needed to first extract the cerebral hemispheres. The detection of the IF is often referred to as mid-sagittal plane estimation, as this plane separates the two cerebral hemispheres. However, traditional planar estimation techniques fail when the IF presents a curvature caused by existing pathology or a natural phenomenon known as brain torque. As a result, midline estimates can be inaccurate. In this study, a fully unsupervised midline estimation technique is proposed that is comprised of three main stages: head angle correction, control point estimation and midline generation. The control points are estimated using a combination of intensity, texture, gradient, and symmetry-based features. As shown, the proposed method automatically adapts to IF curvature, is applied on a slice-to-slice basis for more accurate results and also provides accurate delineation of the midline in the septum pellucidum, which is a source of failure for traditional approaches. The method is compared to two state-of-the-art methods for midline estimation and is validated using 75 imaging volumes (~3,000 imaging slices) acquired from 38 centers of subjects with dementia and vascular disease. The proposed method yields the lowest average error across all metrics: Hausdorff distance (HD) was 0.32 ± 0.23, mean absolute difference (MAD) was 1.10 ± 0.38 mm and volume difference was 7.52 ± 5.40 and 5.35 ± 3.97 ml, for left and right hemispheres, respectively. Using the proposed method, the midline was extracted for 5,360 volumes (~275K images) from 83 centers worldwide, acquired by GE, Siemens and Philips scanners. An asymmetry index was proposed that automatically detected outlier segmentations (which were <1% of the total dataset). Using the extracted hemispheres, hemispheric asymmetry texture biomarkers of the normal-appearing brain matter (NABM) were analyzed in a dementia cohort, and significant differences in biomarker means were found across SCI and MCI and SCI and AD.

Brain Tumor Detection via Asymmetry Quantification across Mid Sagittal Plane

2020 ◽  
Vol 13 ◽  
Author(s):  
Shoaib Amin Banday ◽  
Mohammad Khalid Pandit
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Sagittal Plane ◽  
Early Stage ◽  
Imaging Techniques ◽  
Complex Structure ◽  
Magnetic Resonance Images ◽  
Absolute Difference ◽  
Brain Hemispheres ◽  
The Brain

Introduction: Brain tumor is among the major causes of morbidity and mortality rates worldwide. According to National Brain Tumor Foundation (NBTS), the death rate has nearly increased by as much as 300% over last couple of decades. Tumors can be categorized as benign (non-cancerous) and malignant (cancerous). The type of the brain tumor significantly depends on various factors like the site of its occurrence, its shape, the age of the subject etc. On the other hand, Computer Aided Detection (CAD) has been improving significantly in recent times. The concept, design and implementation of these systems ascend from fairly simple ones to computationally intense ones. For efficient and effective diagnosis and treatment plans in brain tumor studies, it is imperative that an abnormality is detected at an early stage as it provides a little more time for medical professionals to respond. The early detection of diseases has predominantly been possible because of medical imaging techniques developed from past many decades like CT, MRI, PET, SPECT, FMRI etc. The detection of brain tumors however, has always been a challenging task because of the complex structure of the brain, diverse tumor sizes and locations in the brain. Method: This paper proposes an algorithm that can detect the brain tumors in the presence of the Radio-Frequency (RF) inhomoginiety. The algorithm utilizes the Mid Sagittal Plane as a landmark point across which the asymmetry between the two brain hemispheres is estimated using various intensity and texture based parameters. Result: The results show the efficacy of the proposed method for the detection of the brain tumors with an acceptable detection rate. Conclusion: In this paper, we have calculated three textural features from the two hemispheres of the brain viz: Contrast (CON), Entropy (ENT) and Homogeneity (HOM) and three parameters viz: Root Mean Square Error (RMSE), Correlation Co-efficient (CC), and Integral of Absolute Difference (IAD) from the intensity distribution profiles of the two brain hemispheres to predict any presence of the pathology. First a Mid Sagittal Plane (MSP) is obtained on the Magnetic Resonance Images that virtually divides brain into two bilaterally symmetric hemispheres. The block wise texture asymmetry is estimated for these hemispheres using the above 6 parameters.

scholarly journals Myoelectric Control Techniques for a Rehabilitation Robot

2011 ◽  
Vol 8 (1) ◽  
pp. 21-37 ◽  
Author(s):  
Alan Smith ◽  
Edward E. Brown
Keyword(s):  
Healthy Subjects ◽  
Sagittal Plane ◽  
Robot Manipulator ◽  
Wrist Joint ◽  
Elbow Flexion ◽  
Myoelectric Control ◽  
Average Error ◽  
Rehabilitation Robot ◽  
Control Scheme ◽  
Central Cord Syndrome

This work examines two different types of myoelectric control schemes for the purpose of rehabilitation robot applications. The first is a commonly used technique based on a Gaussian classifier. It is implemented in real time for healthy subjects in addition to a subject with Central Cord Syndrome (CCS). The myoelectric control scheme is used to control three degrees of freedom (DOF) on a robot manipulator which corresponded to the robot's elbow joint, wrist joint, and gripper. The classes of motion controlled include elbow flexion and extension, wrist pronation and supination, hand grasping and releasing, and rest. Healthy subjects were able to achieve 90% accuracy. Single DOF controllers were first tested on the subject with CCS and he achieved 100%, 96%, and 85% accuracy for the elbow, gripper, and wrist controllers respectively. Secondly, he was able to control the three DOF controller at 68% accuracy. The potential applications for this scheme are rehabilitation and teleoperation. To overcome limitations in the pattern recognition based scheme, a second myoelectric control scheme is also presented which is trained using electromyographic (EMG) data derived from natural reaching motions in the sagittal plane. This second scheme is based on a time delayed neural network (TDNN) which has the ability to control multiple DOF at once. The controller tracked a subject's elbow and shoulder joints in the sagittal plane. Results showed an average error of 19° for the two joints. This myoelectric control scheme has the potential of being used in the development of exoskeleton and orthotic rehabilitation applications.

scholarly journals Developing a Scene-Based Triangulated Irregular Network (TIN) Technique for Individual Tree Crown Reconstruction with LiDAR Data

Forests ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 28 ◽  
Author(s):  
Haijian Liu ◽  
Changshan Wu
Keyword(s):  
Data Storage ◽  
Shape Control ◽  
Visual Analysis ◽  
Control Point ◽  
Average Error ◽  
Control Points ◽  
Tree Crown ◽  
Individual Tree ◽  
New Model ◽  
Low Pass

LiDAR (Light Detection and Ranging)-based individual tree crown reconstruction is a challenge task due to the variable canopy morphologies and the penetrating properties of LiDAR to tree crown surfaces. Traditional methods, including LiDAR-derived rasterization, low-pass filtering smooth algorithm, and original triangular irregular network (TIN) model, have difficulties in balancing morphological accuracy and model smoothness. To address this issue, a scene-based TIN was generated with three steps based on the local scene principle. First, local Delaunay triangles were formed through connecting neighboring point sets. Second, key control points within each local Delaunay triangle, including steeple, inverted tip, ridge, saddle, and horseshoe shape control points, were extracted by analyzing multiple local scenes. These key points were derived to determine the fluctuations of forest canopies. Third, the scene-based TIN model was generated using the control points as nodes. Visual analysis indicates the new model can accurately reconstruct different canopy shapes with a relatively smooth surface, and statistical analysis of individual trees confirms that the overall error of the new model is smaller than others. Especially, the scene-based TIN derived raster reduced the average error to 0.18 m, with a standard deviation of 0.41, while the average errors of LiDAR-derived raster, low-pass filtered smooth raster, and original TIN derived raster have average errors of 0.96, 2.05, and 1.00 m, respectively. The local scene-based control point extraction also reduces data storage due to the elimination of redundant points, and furthermore the different point densities on different objects are beneficial for canopy segmentation.

scholarly journals Limitations and ceiling effects with circumferential minimally invasive correction techniques for adult scoliosis: analysis of radiological outcomes over a 7-year experience

2014 ◽  
Vol 36 (5) ◽  
pp. E14 ◽  
Author(s):  
Neel Anand ◽  
Eli M. Baron ◽  
Babak Khandehroo
Keyword(s):  
Minimally Invasive ◽  
Cobb Angle ◽  
Lumbar Lordosis ◽  
Sagittal Plane ◽  
Adult Scoliosis ◽  
Angle Correction ◽  
Scoliosis Correction ◽  
Spinopelvic Parameter ◽  
Ceiling Effects ◽  
The Mean

Object Minimally invasive correction of adult scoliosis is a surgical method increasing in popularity. Limited data exist, however, as to how effective these methodologies are in achieving coronal plane and sagittal plane correction in addition to improving spinopelvic parameters. This study serves to quantify how much correction is possible with present circumferential minimally invasive surgical (cMIS) methods. Methods Ninety patients were selected from a database of 187 patients who underwent cMIS scoliosis correction. All patients had a Cobb angle greater than 15°, 3 or more levels fused, and availability of preoperative and postoperative 36-inch standing radiographs. The mean duration of follow-up was 37 months. Preoperative and postoperative Cobb angle, sagittal vertical axis (SVA), coronal balance, lumbar lordosis (LL), and pelvic incidence (PI) were measured. Scatter plots were performed comparing the pre- and postoperative radiological parameters to calculate ceiling effects for SVA correction, Cobb angle correction, and PI-LL mismatch correction. Results The mean preoperative SVA value was 60 mm (range 11.5–151 mm); the mean postoperative value was 31 mm (range 0–84 mm). The maximum SVA correction achieved with cMIS techniques in any of the cases was 89 mm. In terms of coronal Cobb angle, a mean correction of 61% was noted, with a mean preoperative value of 35.8° (range 15°–74.7°) and a mean postoperative value of 13.9° (range 0°–32.5°). A ceiling effect for Cobb angle correction was noted at 42°. The ability to correct the PI-LL mismatch to 10° was limited to cases in which the preoperative PI-LL mismatch was 38° or less. Conclusions Circumferential MIS techniques as currently used for the treatment of adult scoliosis have limitations in terms of their ability to achieve SVA correction and lumbar lordosis. When the preoperative SVA is greater than 100 mm and a substantial amount of lumbar lordosis is needed, as determined by spinopelvic parameter calculations, surgeons should consider osteotomies or other techniques that may achieve more lordosis.

scholarly journals An Evaluation of Symmetry in the Lower Limb Joints During the Able-Bodied Gait of Women and Men

2012 ◽  
Vol 35 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Wanda Forczek ◽  
Robert Staszkiewicz
Keyword(s):  
Lower Limb ◽  
Sagittal Plane ◽  
Temporal Structure ◽  
Asymmetry Index ◽  
Lower Limbs ◽  
Inclusion Criteria ◽  
3D Motion Analysis ◽  
Spatio Temporal ◽  
Analysis System ◽  
The Right

For many years, mainly to simplify data analysis, scientists assumed that during a gait, the lower limbs moved symmetrically. However, even a cursory survey of the more recent literature reveals that the human walk is symmetrical only in some aspects. That is why the presence of asymmetry should be considered in all studies of locomotion. The gait data were collected using the 3D motion analysis system Vicon. The inclusion criteria allowed the researchers to analyze a very homogenous group, which consisted of 54 subjects (27 women and 27 men). Every selected participant moved at a similar velocity: approximately 1,55 m/s. The analysis included kinematic parameters defining spatio-temporal structure of locomotion, as well as angular changes of the main joints of the lower extremities (ankle, knee and hip) in the sagittal plane. The values of those variables were calculated separately for the left and for the right leg in women and men. This approach allowed us to determine the size of the differences, and was the basis for assessing gait asymmetry using a relative asymmetry index, which was constructed by the authors. Analysis of the results demonstrates no differences in the temporal and phasic variables of movements of the right and left lower limb. However, different profiles of angular changes in the sagittal plane were observed, measured bilaterally for the ankle joint.

scholarly journals Effects of Exercise Intensity on Pedal Force Asymmetry during Cycling

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1449
Author(s):  
John Wayland Farrell ◽  
Brian A. Pribble ◽  
Rebecca D. Larson
Keyword(s):  
Blood Lactate ◽  
Exercise Intensity ◽  
Test Group ◽  
Asymmetry Index ◽  
Lower Limbs ◽  
Absolute Difference ◽  
Peak Power Output ◽  
Pedal Force ◽  
Main Effect ◽  
Power Outputs

The purpose of the current investigation was to examine the effects of exercise intensity and a participant’s cycling experience on asymmetry in pedal forces during cycling. Participants were classified as cycling experienced (CE) or non-cycling experienced (NCE) based on self-reported training history. Participants completed an incremental cycling test via a cycle ergometer with inspired and expired gases, capillary blood lactate and pedaling forces collected throughout the test. Group X exercise intensity comparisons were analyzed at workloads corresponding to 2 mmol/L and 4 mmol/L for the blood lactate accumulation and peak power output, respectively. No Group X exercise intensity interactions for any variables (p > 0.05) were observed. The main effect on the exercise intensity was observed for absolute (p = 0.000, η2 = 0.836) and relative (p = 0.000, η2 = 0.752) power outputs and pedal force effectiveness (PFE) (p = 0.000, η2 = 0.728). The main effect for the group was observed for absolute (p = 0.007, η2 = 0.326) and relative (p = 0.001, η2 = 0.433) power outputs, the absolute difference between the lower limbs in power production (p = 0.047, η2 = 0.191), the peak crank torque asymmetry index (p = 0.031, η2 = 0.222) and the PFE (p = 0.014, η2 = 0.280). The exercise intensity was observed to have no impact on asymmetry in pedaling forces during cycling.

Reconstruction of Experimental Hyperthermia Temperature Distributions: Application of State and Parameter Estimation

1993 ◽  
Vol 115 (4A) ◽  
pp. 380-388 ◽  
Author(s):  
S. T. Clegg ◽  
R. B. Roemer
Keyword(s):  
Parameter Estimation ◽  
Steady State ◽  
Temperature Distribution ◽  
Estimation Algorithm ◽  
Absolute Difference ◽  
Average Error ◽  
Measured Temperature ◽  
Data Set ◽  
Power Deposition ◽  
Reconstructed Temperature

Subsets of data from spatially sampled temperatures measured in each of nine experimental heatings of normal canine thighs were used to test the feasibility of using a state and parameter estimation (SPE) technique to predict the complete measured data set in each heating. Temperature measurements were made at between seventy-two and ninety-six stationary thermocouple locations within the thigh, and measurements from as few as thirteen of these locations were used as inputs to the estimation algorithm. The remaining (non “input”) measurements were compared to the predicted temperatures for the corresponding “unmeasured” locations to judge the ability of the estimation algorithm to accurately reconstruct the complete experimental data set. The results show that the predictions of the “unmeasured” steady-state temperatures are quite accurate in general (average errors usually < 0.5°C; and small variances about those averages) and that this reconstruction procedure can yield improved descriptors of the steady-state temperature distribution. The accuracy of the reconstructed temperature distribution was not strongly affected by either the number of perfusion zones or by the number of input sensors used by the algorithm. One situation extensively considered in this study modeled the thigh with twenty-seven independent regions of perfusion. For this situation, measurements from ninety-six to thirteen sensors were used as input to the estimation algorithm. The average error for all of these cases ranged from −0.55°C to +0.75°C, respectively, and was not strongly related to the number of sensors used as input to the estimation algorithm. For these same cases the maximum prediction error (the maximum absolute difference between the measured temperature and the predicted temperature determined by a search over all locations) ranged from 0.92°C to 5.08°C, respectively. To attempt to explain the magnitude of the maximum error, several possible sources of model mismatch and of experimental uncertainty were considered. For this study, a significant source of error appears to arise from differences between the true power deposition field, the power deposition model predictions, and the experimentally measured powers. In summary, while large errors can be present for a few isolated locations in the predicted temperature fields, the SPE algorithm can accurately predict the average characteristics of the temperature field. This predictive ability should be clinically useful.

Prediction of ischial ramal angle for transfemoral ischial containment sockets

2018 ◽  
Vol 43 (1) ◽  
pp. 39-46
Author(s):  
Matthew Quigley ◽  
Michael P Dillon ◽  
Richard GD Fernandez ◽  
Bircan Erbas ◽  
Chris Briggs
Keyword(s):  
Regression Models ◽  
Sagittal Plane ◽  
Cross Sectional Study ◽  
Average Error ◽  
Cross Sectional ◽  
In Vivo Measurement ◽  
Knowing That ◽  
Significant Difference ◽  
Computed Tomography Scans

Background: A well-fitting and comfortable ischial containment socket relies on accurately replicating the transverse plane angle of the ischium and ischial ramus angle, inside the medial socket brim. Prediction of the ischial ramus angle, may provide a way to determine the ischial ramus angle without in vivo measurement. Objectives: To determine the accuracy with which the ischial ramus angle could be predicted and identify which variables contributed significantly to the prediction. Study design: Cross-sectional study. Methods: Computed tomography scans were randomly sampled from a cadaveric database (n = 200). Standard multiple regression models were developed to predict the ischial ramus angle based on pelvic measures. Results: The regression model explained 10.5% of the variance in ischial ramus angle (p = 0.018). The standard error of the estimate was 11.32°. While regression models by sex explained a larger proportion of the variance, the resulting accuracy was not improved. Conclusion: The regression models explained a small proportion of variance in ischial ramus angle. The average error associated with the prediction was too large to accurately predict the ischial ramus angle for use in clinical practice. Contrary to commonly held beliefs, there was no statistically significant difference in ischial ramus angle between sexes. Clinical relevance Prediction of ischial ramus angle does not have sufficient accuracy to be clinically useful, but descriptive data may help clinicians identify casting errors and correct these in a plaster positive, knowing that the average ischial ramus angle was 32.65°±5.59° (relative to mid-sagittal plane) and does not vary between sexes.

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