The interutricular distance determined from external landmarks

2003 ◽  
Vol 13 (1) ◽  
pp. 17-23
Author(s):  
Vicky Nowé ◽  
Floris L. Wuyts ◽  
Mieke Hoppenbrouwers ◽  
Paul H. Van de Heyning ◽  
Arthur M. De Schepper ◽  
...  
Keyword(s):  
Constant Velocity ◽  
Prediction Interval ◽  
Magnetic Resonance Images ◽  
Mr Images ◽  
Vestibular Tests ◽  
Axis Of Rotation ◽  
Precise Knowledge ◽  
Temporomandibular Joints ◽  
Lateral Margins ◽  
Unilateral Centrifugation

Knowledge of the exact distance between the utricles is important in new vestibular tests, such as the unilateral centrifugation (UC) test for the unilateral examination of the utricles. During this test, subjects are rotated at constant velocity and simultaneously laterally displaced along an interaural axis so that one labyrinth becomes aligned with the axis of rotation. When the axis of rotation crosses precisely through one labyrinth, only the opposite labyrinth is stimulated. To achieve this setup, precise knowledge of the interutricular distance is needed. The purpose of this study is to investigate the correlation between the interutricular distance (IUD), measured on T2-weighted magnetic resonance images, and specific external measures of head dimensions such as distance nasion-inion, intermastoid distance (IMD), distances between the temporomandibular joints and between the lateral margins of the orbits. Data have been collected in a series of 50 subjects (25 men and 25 women). On MR images we found a mean IUD of 7.22 cm ( S D = 0.42 cm). There was a strong correlation between the IUD measured on MR images and the intermastoid distance. A linear combination of the IMD, nasion-inion distance and height of the subjects could predict the IUD very satisfactory (R=0.85, adjusted R 2 = 0.723). We also determined a measure of eccentricity of the vestibular labyrinths. The 95% prediction interval for the asymmetry appeared to be less than 4.3%.

scholarly journals Automated Head Tissue Modelling Based on Structural Magnetic Resonance Images for Electroencephalographic Source Reconstruction

2021 ◽  
Author(s):  
Gaia Amaranta Taberna ◽  
Jessica Samogin ◽  
Dante Mantini
Keyword(s):  
Magnetic Resonance ◽  
Brain Structures ◽  
Magnetic Resonance Images ◽  
Head Model ◽  
Source Reconstruction ◽  
Mr Images ◽  
Tissue Segmentation ◽  
Mr Image ◽  
Eeg Recordings ◽  
Tissue Modelling

AbstractIn the last years, technological advancements for the analysis of electroencephalography (EEG) recordings have permitted to investigate neural activity and connectivity in the human brain with unprecedented precision and reliability. A crucial element for accurate EEG source reconstruction is the construction of a realistic head model, incorporating information on electrode positions and head tissue distribution. In this paper, we introduce MR-TIM, a toolbox for head tissue modelling from structural magnetic resonance (MR) images. The toolbox consists of three modules: 1) image pre-processing – the raw MR image is denoised and prepared for further analyses; 2) tissue probability mapping – template tissue probability maps (TPMs) in individual space are generated from the MR image; 3) tissue segmentation – information from all the TPMs is integrated such that each voxel in the MR image is assigned to a specific tissue. MR-TIM generates highly realistic 3D masks, five of which are associated with brain structures (brain and cerebellar grey matter, brain and cerebellar white matter, and brainstem) and the remaining seven with other head tissues (cerebrospinal fluid, spongy and compact bones, eyes, muscle, fat and skin). Our validation, conducted on MR images collected in healthy volunteers and patients as well as an MR template image from an open-source repository, demonstrates that MR-TIM is more accurate than alternative approaches for whole-head tissue segmentation. We hope that MR-TIM, by yielding an increased precision in head modelling, will contribute to a more widespread use of EEG as a brain imaging technique.

scholarly journals Multigrid Nonlocal Gaussian Mixture Model for Segmentation of Brain Tissues in Magnetic Resonance Images

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Yunjie Chen ◽  
Tianming Zhan ◽  
Ji Zhang ◽  
Hongyuan Wang
Keyword(s):  
Magnetic Resonance ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Magnetic Resonance Images ◽  
Intensity Inhomogeneity ◽  
Mr Images ◽  
Proposed Model ◽  
Brain Mr Images ◽  
The Impact

We propose a novel segmentation method based on regional and nonlocal information to overcome the impact of image intensity inhomogeneities and noise in human brain magnetic resonance images. With the consideration of the spatial distribution of different tissues in brain images, our method does not need preestimation or precorrection procedures for intensity inhomogeneities and noise. A nonlocal information based Gaussian mixture model (NGMM) is proposed to reduce the effect of noise. To reduce the effect of intensity inhomogeneity, the multigrid nonlocal Gaussian mixture model (MNGMM) is proposed to segment brain MR images in each nonoverlapping multigrid generated by using a new multigrid generation method. Therefore the proposed model can simultaneously overcome the impact of noise and intensity inhomogeneity and automatically classify 2D and 3D MR data into tissues of white matter, gray matter, and cerebral spinal fluid. To maintain the statistical reliability and spatial continuity of the segmentation, a fusion strategy is adopted to integrate the clustering results from different grid. The experiments on synthetic and clinical brain MR images demonstrate the superior performance of the proposed model comparing with several state-of-the-art algorithms.

Reducing susceptibility artefacts in magnetic resonance images of the canine stifle following surgery for cranial cruciate ligament deficiency

2012 ◽  
Vol 25 (06) ◽  
pp. 488-497 ◽  
Author(s):  
J. Grierson ◽  
C. R. Lamb ◽  
F. H. David
Keyword(s):  
Magnetic Resonance ◽  
Tibial Plateau ◽  
Cruciate Ligament ◽  
Magnetic Resonance Images ◽  
Proton Density ◽  
Mr Images ◽  
Cranial Cruciate Ligament ◽  
Metallic Implants ◽  
Image Ranking ◽  
Canine Stifle

SummaryBackground: Magnetic resonance (MR) images of the postoperative canine stifle are adversely affected by susceptibility artefacts associated with metallic implants.Objectives: To determine empirically to what extent susceptibility artefacts could be reduced by modifications to MR technique.Methods: Three cadaveric limbs with a tibial plateau levelling osteotomy (TPLO), tibial tuberosity advancement (TTA), or extra-capsular stabilization (ECS) implant, respectively, were imaged at 1.5T. Series of proton density and T2-weighted images were acquired with different combinations of frequency-encoding gradient (FEG) direction and polarity, stifle flexion or extension, echo spacing (ES), and readout bandwidth (ROBW), and ranked. The highest rank (a rank of 1) corresponded to the smallest artefact.Results: Image ranking was affected by FEG polarity (p = 0.005), stifle flexion (p = 0.01), and ROBW (p = 0.0001). For TPLO and TTA implants, the highest ranked images were obtained with the stifle flexed, lateromedial FEG, and medial polarity for dorsal images, and craniocaudal FEG and caudal polarity for sagittal images. For the ECS implant, the highest ranked images were obtained with the stifle extended, a proximodistal FEG and proximal polarity for dorsal images, and craniocaudal FEG and cranial polarity for sagittal images.Clinical significance: Susceptibility artefacts in MR images of postoperative canine stifles do not preclude clinical evaluation of joints with ECS or TTA implants.Part of this study was presented at the Annual Meeting of the American College of Veterinary Radiology, Albuquerque, NM, October 2011.

Temporomandibular Joint Imaging

2020 ◽  
pp. 582-697
Author(s):  
Mark Piper, DMD MD
Keyword(s):  
Magnetic Resonance ◽  
Soft Tissue ◽  
Temporomandibular Joint ◽  
Mr Images ◽  
Anatomical Structures ◽  
Temporomandibular Joints ◽  
Key Concepts ◽  
Masticatory System ◽  
The Relationship ◽  
Insight Into

Computerized tomography (CT) and magnetic resonance (MR) imaging of the temporomandibular joint are often not a routine part of a dental patient's pain and clinical evaluation. As a result, the most poorly understood region within the masticatory system is the temporomandibular joint foundation. Unfortunately, patient care and occlusal management are often compromised because of a lack of insight into the relationship between the anatomy of the temporomandibular joints and the occlusion. This chapter's four distinct sections review the key concepts about the temporomandibular joint foundation anatomical structures, detail structurally intact and structurally altered temporomandibular joint anatomy, clarify how structurally altered temporomandibular joints influence occlusal function, and classify the stages of temporomandibular joint structural degeneration. The concept of joint-based malocclusion is explored with numerous temporomandibular joint foundation anomalous software renderings, and sample CT and MR images, which together illustrate in detail how soft tissue and bony abnormalities in a structurally altered temporomandibular joint can create distortions in the occlusion. Lastly, the chapter addresses the specific requirements a clinician must technically master to perform a comprehensive CT or MR examination.

scholarly journals Interobserver variability in quality assessment of magnetic resonance images

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Rafal Obuchowicz ◽  
Mariusz Oszust ◽  
Adam Piorkowski
Keyword(s):  
Magnetic Resonance ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Interobserver Variability ◽  
Poor Performance ◽  
Magnetic Resonance Images ◽  
Perceptual Quality ◽  
Mr Images

Abstract Background The perceptual quality of magnetic resonance (MR) images influences diagnosis and may compromise the treatment. The purpose of this study was to evaluate how the image quality changes influence the interobserver variability of their assessment. Methods For the variability evaluation, a dataset containing distorted MRI images was prepared and then assessed by 31 experienced medical professionals (radiologists). Differences between observers were analyzed using the Fleiss’ kappa. However, since the kappa evaluates the agreement among radiologists taking into account aggregated decisions, a typically employed criterion of the image quality assessment (IQA) performance was used to provide a more thorough analysis. The IQA performance of radiologists was evaluated by comparing the Spearman correlation coefficients, ρ, between individual scores with the mean opinion scores (MOS) composed of the subjective opinions of the remaining professionals. Results The experiments show that there is a significant agreement among radiologists (κ=0.12; 95% confidence interval [CI]: 0.118, 0.121; P<0.001) on the quality of the assessed images. The resulted κ is strongly affected by the subjectivity of the assigned scores, separately presenting close scores. Therefore, the ρ was used to identify poor performance cases and to confirm the consistency of the majority of collected scores (ρmean = 0.5706). The results for interns (ρmean = 0.6868) supports the finding that the quality assessment of MR images can be successfully taught. Conclusions The agreement observed among radiologists from different imaging centers confirms the subjectivity of the perception of MR images. It was shown that the image content and severity of distortions affect the IQA. Furthermore, the study highlights the importance of the psychosomatic condition of the observers and their attitude.

scholarly journals Multicomponent MR Image Denoising

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
José V. Manjón ◽  
Neil A. Thacker ◽  
Juan J. Lull ◽  
Gracian Garcia-Martí ◽  
Luís Martí-Bonmatí ◽  
...  
Keyword(s):  
Random Noise ◽  
Principal Component ◽  
Magnetic Resonance Images ◽  
Image Resolution ◽  
Single Image ◽  
Mr Images ◽  
Mr Image ◽  
Automatic Feature Extraction ◽  
Improved Performance ◽  
Multicomponent Nature

Magnetic Resonance images are normally corrupted by random noise from the measurement process complicating the automatic feature extraction and analysis of clinical data. It is because of this reason that denoising methods have been traditionally applied to improve MR image quality. Many of these methods use the information of a single image without taking into consideration the intrinsic multicomponent nature of MR images. In this paper we propose a new filter to reduce random noise in multicomponent MR images by spatially averaging similar pixels using information from all available image components to perform the denoising process. The proposed algorithm also uses a local Principal Component Analysis decomposition as a postprocessing step to remove more noise by using information not only in the spatial domain but also in the intercomponent domain dealing in a higher noise reduction without significantly affecting the original image resolution. The proposed method has been compared with similar state-of-art methods over synthetic and real clinical multicomponent MR images showing an improved performance in all cases analyzed.

scholarly journals Effusion attenuates the effect of synovitis on radiographic progression in patients with hand osteoarthritis: a longitudinal magnetic resonance imaging study

2020 ◽  
Vol 40 (1) ◽  
pp. 315-319
Author(s):  
W. Damman ◽  
R. Liu ◽  
M. Reijnierse ◽  
F. R. Rosendaal ◽  
J. L. Bloem ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Radiographic Progression ◽  
Imaging Study ◽  
Magnetic Resonance Images ◽  
High Signal ◽  
Hand Osteoarthritis ◽  
Mr Images ◽  
Contrast Enhanced ◽  
Key Points

AbstractAn exploratory study to determine the role of effusion, i.e., fluid in the joint, in pain, and radiographic progression in patients with hand osteoarthritis. Distal and proximal interphalangeal joints (87 patients, 82% women, mean age 59 years) were assessed for pain. T2-weighted and Gd-chelate contrast-enhanced T1-weighted magnetic resonance images were scored for enhanced synovial thickening (EST, i.e., synovitis), effusion (EST and T2-high signal intensity [hsi]) and bone marrow lesions (BMLs). Effusion was defined as follows: (1) T2-hsi > 0 and EST = 0; or 2) T2-hsi = EST but in different joint locations. Baseline and 2-year follow-up radiographs were scored following Kellgren-Lawrence, increase ≥ 1 defined progression. Associations between the presence of effusion and pain and radiographic progression, taking into account EST and BML presence, were explored on the joint level. Effusion was present in 17% (120/691) of joints, with (63/120) and without (57/120) EST. Effusion on itself was not associated with pain or progression. The association with pain and progression, taking in account other known risk factors, was stronger in the absence of effusion (OR [95% CI] 1.7 [1.0–2.9] and 3.2 [1.7–5.8]) than in its presence (1.6 [0.8–3.0] and 1.3 [0.5–3.1]). Effusion can be assessed on MR images and seems not to be associated with pain or radiographic progression but attenuates the association between synovitis and progression. Key Points• Effusion is present apart from synovitis in interphalangeal joints in patients with hand OA.• Effusion in finger joints can be assessed as a separate feature on MR images.• Effusion seems to be of importance for its attenuating effect on the association between synovitis and radiographic progression.

Cerebral Contour Extraction with Particle Method in Neonatal MR Images

2011 ◽  
Vol 15 (3) ◽  
pp. 362-369
Author(s):  
Syoji Kobashi ◽  
◽  
Daisuke Yokomichi ◽  
Yuki Wakata ◽  
Kumiko Ando ◽  
...  
Keyword(s):  
Ground Truth ◽  
Particle Method ◽  
Magnetic Resonance Images ◽  
Mean Square ◽  
Contour Extraction ◽  
Mr Images ◽  
Basic Work ◽  
Brain Mr Images ◽  
Method Of Extraction ◽  
The Brain

Cerebral surface extraction from neonatal MR images is the basic work of quantifying the deformation of the cerebrum. Although there are many conventional methods of segmenting the cerebral region, only the rough area is given by counting the number of surface voxels in the segmented region. This article proposes a new method of extraction that is based on the particle method. The method introduces three kinds of particles that correspond to cerebrospinal fluid, gray matter, and white matter; it converts the brain MR images into the set of particles. The proposed method was applied to neonatal magnetic resonance images, and the experimental results showed that the cerebral contour was extracted with a root-mean-square-error of 0.51 mm compared with the ground truth contour given by a physician.

Computer Aided Interpretation of Fibrous Texture in Hepatic Magnetic Resonance Images

2013 ◽  
Vol 647 ◽  
pp. 325-330 ◽  
Author(s):  
Yu Fan Zeng ◽  
Xue Jun Zhang ◽  
Wen Yan ◽  
Li Ling Long ◽  
Yu Kun Huang ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Hepatic Fibrosis ◽  
Region Of Interest ◽  
Texture Features ◽  
Magnetic Resonance Images ◽  
Optimal Number ◽  
Support Vector ◽  
Mr Images ◽  
Accuracy Rate ◽  
Occurrence Matrix

The fibrous texture in liver is one of important signs for interpreting the chronic liver diseases in radiologists’ routines. In order to investigate the usefulness of various texture features calculated by computer algorithm on hepatic magnetic resonance (MR) images, 15 texture features were calculated from the gray level co-occurrence matrix (GLCM) within a region of interest (ROI) which was selected from the MR images with 6 stages of hepatic fibrosis. By different combination of 15 features as input vectors, the classifier had different performance in staging the hepatic fibrosis. Each combination of texture features was tested by Support Vector Machine (SVM) with leave one case out method. 173 patients’ MR images including 6 stages of hepatic fibrosis were scanned within recent two years. The result showed that optimal number of features was confirmed from 3 to 7 by investigating the classified accuracy rate between each stage/group. It is evident that angular second moment, entropy, sum average and sum entropy played the most significant role in classification.

Interpretation of magnetic resonance images in diffuse intrinsic pontine glioma: a survey of pediatric neurosurgeons

2011 ◽  
Vol 8 (1) ◽  
pp. 97-102 ◽  
Author(s):  
Todd C. Hankinson ◽  
Elizabeth J. Campagna ◽  
Nicholas K. Foreman ◽  
Michael H. Handler
Keyword(s):  
Mr Imaging ◽  
Online Survey ◽  
Multicenter Trial ◽  
Diffuse Intrinsic Pontine Glioma ◽  
Magnetic Resonance Images ◽  
Imaging Findings ◽  
Mr Images ◽  
Pontine Glioma ◽  
Tumor Biopsy ◽  
Imaging Characteristics

Object The current management paradigm for children with newly diagnosed diffuse intrinsic pontine glioma (DIPG) is to establish a diagnosis and begin therapy based on MR imaging findings correlated with an appropriate clinical presentation, and without a tissue diagnosis. This strategy assumes that pediatric neurosurgeons and neurooncologists uniformly interpret MR imaging findings in this population. This study sought to examine the consistency of North American pediatric neurosurgeons in assessing MR images in this patient population, and in their surgical plans based on the interpretation of those images. Methods The authors created an online survey and invited all members of the American Society of Pediatric Neurosurgeons and the American Association of Neurological Surgeons/Congress of Neurological Surgeons Joint Section for Pediatric Neurosurgery to participate. The survey consisted of 58 questions, and 48 pertained to representative MR images from 16 children who presented to The Children's Hospital of Colorado with diffuse pontine tumors. Based on the imaging presented and a standard clinical scenario, the respondent was asked if she or he believed a lesion to be “typical” or “atypical,” whether she or he would biopsy the lesion, and what surgical approach would be chosen. The remaining 10 questions pertained to respondent demographics and his or her practice regarding tissue preservation and interest in participating in a multicenter trial that included tumor biopsy in selected cases. Rates at which each lesion was considered to be typical or atypical and rates of recommended biopsy were calculated. Results Surveys were received by 269 individuals. Eighty-six responses were received (32.0%). No tumor was judged to be either typical or atypical by all respondents. Individual surgeons varied widely regarding how many of the tumors were judged as typical or warranted a biopsy. The percentage of respondents who disagreed with the majority opinion regarding whether a tumor qualified as typical ranged from 2.3% to 48.8%, with a median of 28.6%. More than 75% agreement regarding whether a tumor was typical or atypical was found in 7 (43.8%) of 16 cases. The κ statistic regarding typicality was 0.297 ± 0.0004 (mean ± SEM), implying only fair agreement. For every tumor, at least 1 respondent who believed the lesion to be typical in appearance would nevertheless biopsy the lesion. Of those respondents who considered a lesion to be typical, a median of 5.1% (range 1.2%–66.7%) would choose to biopsy this lesion. Of those respondents who considered a lesion atypical, a median of 18.3% (range 3.7%–100%) would choose not to biopsy the lesion. Of 85 responses to the question, “Would you be willing to biopsy a typical diffuse pontine glioma as a part of a multicenter trial?,” 59 (69.4%) of 85 respondents answered that they would. Conclusions Although making a diagnosis based on radiographic evidence alone represents a well-established management paradigm for children with suspected DIPG, this study demonstrates considerable inconsistency on the part of pediatric neurosurgeons in the application of this strategy to individual patients. As such, the practice of diagnosing DIPG based on imaging characteristics and clinical history alone does not reach the appropriate threshold to be considered a standard of care.

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