scholarly journals A Simple Approach for Relatively Automated Hippocampus Segmentation from Sagittal View of Brain MRI

2016 ◽  
Vol 6 (2) ◽  
pp. 23-30
Author(s):  
Vijayalakshmi S ◽  
Prabha S. Nair ◽  
Durgadevi P
Keyword(s):  
Brain Mri ◽  
Simple Approach ◽  
Hippocampus Segmentation

scholarly journals Semi-automated Approach to Hippocampus Segmentation Using Snake from Brain MRI

2014 ◽  
Vol 17 (5) ◽  
pp. 566-572 ◽  
Author(s):  
Ala'a Ddin Al Shidaifat ◽  
Ramadan Al-Shdefat ◽  
Heung-Kook Choi
Keyword(s):  
Brain Mri ◽  
Hippocampus Segmentation

scholarly journals Hippocampus Segmentation Method Based on Subspace Patch-Sparsity Clustering in Noisy Brain MRI

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaogang Ren ◽  
Yue Wu ◽  
Zhiying Cao
Keyword(s):  
Brain Mri ◽  
Coefficient Matrix ◽  
Experimental Results ◽  
Irregular Shape ◽  
Segmentation Method ◽  
Sparse Constraint ◽  
Low Contrast ◽  
Segmentation Accuracy ◽  
Hippocampus Segmentation ◽  
Segmentation Problem

Since the hippocampus is of small size, low contrast, and irregular shape, a novel hippocampus segmentation method based on subspace patch-sparsity clustering in brain MRI is proposed to improve the segmentation accuracy, which requires that the representation coefficients in different subspaces should be as sparse as possible, while the representation coefficients in the same subspace should be as average as possible. By restraining the coefficient matrix with the patch-sparse constraint, the coefficient matrix contains a patch-sparse structure, which is helpful to the hippocampus segmentation. The experimental results show that our proposed method is effective in the noisy brain MRI data, which can well deal with hippocampus segmentation problem.

Influence of X-Ray Induced Fluorescence on Energy Dispersive X-Ray Analysis of Thin Foils

1977 ◽  
Vol 35 ◽  
pp. 328-329
Author(s):  
E. A. Kenik ◽  
J. Bentley
Keyword(s):  
Thin Foil ◽  
Electron Excitation ◽  
Simple Approach ◽  
Foil Thickness ◽  
X Rays ◽  
X Ray ◽  
Hole Spectrum ◽  
Illumination System ◽  
Thin Foils ◽  
Intensity Ratios

Cliff and Lorimer (1) have proposed a simple approach to thin foil x-ray analy sis based on the ratio of x-ray peak intensities. However, there are several experimental pitfalls which must be recognized in obtaining the desired x-ray intensities. Undesirable x-ray induced fluorescence of the specimen can result from various mechanisms and leads to x-ray intensities not characteristic of electron excitation and further results in incorrect intensity ratios.In measuring the x-ray intensity ratio for NiAl as a function of foil thickness, Zaluzec and Fraser (2) found the ratio was not constant for thicknesses where absorption could be neglected. They demonstrated that this effect originated from x-ray induced fluorescence by blocking the beam with lead foil. The primary x-rays arise in the illumination system and result in varying intensity ratios and a finite x-ray spectrum even when the specimen is not intercepting the electron beam, an ‘in-hole’ spectrum. We have developed a second technique for detecting x-ray induced fluorescence based on the magnitude of the ‘in-hole’ spectrum with different filament emission currents and condenser apertures.

Complex Subject : Simple Approach

2004 ◽  
Vol 49 (4) ◽  
pp. 401-403
Author(s):  
Richard B. Makover
Keyword(s):  
Simple Approach ◽  
Complex Subject

USEFULNESS OF BRAIN MRI IN DIAGNOSIS OF NBIA IN PKAN AND NON-PKAN PATIENTS

2006 ◽  
Vol 37 (S 1) ◽  
Author(s):  
T Kmiec ◽  
E Jurkiewicz ◽  
S Jozwiak ◽  
I Pakula-Kosciesza ◽  
M Ebhart ◽  
...  
Keyword(s):  
Brain Mri

Brain MRI-findings in Ph - negative myeloproliferative disorders

2019 ◽  
Vol 91 (7) ◽  
pp. 29-34 ◽  
Author(s):  
M M Tanashyan ◽  
A L Melikyan ◽  
P I Kuznetsova ◽  
A A Raskurazhev ◽  
A A Shabalina ◽  
...  
Keyword(s):  
Cerebrovascular Disease ◽  
Sinus Thrombosis ◽  
Cerebral Arteries ◽  
Brain Mri ◽  
Myeloproliferative Disorders ◽  
Cerebral Venous Sinus Thrombosis ◽  
Mri Findings ◽  
Cerebral Lesions ◽  
Cerebrovascular Pathology ◽  
Underlying Mechanisms

Myeloproliferative disorders (MPD) are accompanied by a high proportion of thrombotic complications, which may lead to cerebrovascular disease (CVD). Aim. To describe MRI-findings in patients with Ph - negative MPD and evaluate any cerebrovascular disease. Materials and methods. We included 104 patients with Ph - negative MPD (age varied between 20 and 58) with clinical correlates of cerebrovascular pathology. Results. Brain MRI showed post - stroke lesions in 20% of patients (7 hemispheric infarcts due to thrombotic occlusion of one of the large cerebral arteries, 14 - cortical infarcts). 37 patients (36%) had vascular cerebral lesions. Cerebral venous sinus thrombosis occurred in 5 patients - in 7% (n=3) of patients with polycythemia vera and 5% (n=2) - in patients with essential thrombocythemia. The incidence of vascular cerebral lesions was associated with higher levels of the following: erythrocyte, platelet count, fibrinogen, and with the decrease in fibrinolytic activity, as well. Conclusion. The pioneering results of the study include the description and analysis of brain MRI-findings in patients with Ph - negative MPD. The underlying mechanisms of cerebrovascular pathology in these patients are associated with certain blood alterations (particularly, hemorheology) which present a major risk factor.

Normal cerebral ventricular volume growth in childhood

2020 ◽  
Vol 26 (5) ◽  
pp. 517-524
Author(s):  
Noah S. Cutler ◽  
Sudharsan Srinivasan ◽  
Bryan L. Aaron ◽  
Sharath Kumar Anand ◽  
Michael S. Kang ◽  
...  
Keyword(s):  
Brain Mri ◽  
Volume Growth ◽  
Ventricular Volume ◽  
Growth Patterns ◽  
Diagnostic Process ◽  
Growth Charts ◽  
Normal Brain ◽  
Mr Images ◽  
Ventricular Volumes ◽  
Brain Mr Images

OBJECTIVENormal percentile growth charts for head circumference, length, and weight are well-established tools for clinicians to detect abnormal growth patterns. Currently, no standard exists for evaluating normal size or growth of cerebral ventricular volume. The current standard practice relies on clinical experience for a subjective assessment of cerebral ventricular size to determine whether a patient is outside the normal volume range. An improved definition of normal ventricular volumes would facilitate a more data-driven diagnostic process. The authors sought to develop a growth curve of cerebral ventricular volumes using a large number of normal pediatric brain MR images.METHODSThe authors performed a retrospective analysis of patients aged 0 to 18 years, who were evaluated at their institution between 2009 and 2016 with brain MRI performed for headaches, convulsions, or head injury. Patients were excluded for diagnoses of hydrocephalus, congenital brain malformations, intracranial hemorrhage, meningitis, or intracranial mass lesions established at any time during a 3- to 10-year follow-up. The volume of the cerebral ventricles for each T2-weighted MRI sequence was calculated with a custom semiautomated segmentation program written in MATLAB. Normal percentile curves were calculated using the lambda-mu-sigma smoothing method.RESULTSVentricular volume was calculated for 687 normal brain MR images obtained in 617 different patients. A chart with standardized growth curves was developed from this set of normal ventricular volumes representing the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. The charted data were binned by age at scan date by 3-month intervals for ages 0–1 year, 6-month intervals for ages 1–3 years, and 12-month intervals for ages 3–18 years. Additional percentile values were calculated for boys only and girls only.CONCLUSIONSThe authors developed centile estimation growth charts of normal 3D ventricular volumes measured on brain MRI for pediatric patients. These charts may serve as a quantitative clinical reference to help discern normal variance from pathologic ventriculomegaly.

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