scholarly journals Multi-Sectional Views Textural Based SVM for MS Lesion Segmentation in Multi-Channels MRIs

2012 ◽  
Vol 6 (1) ◽  
pp. 56-72 ◽  
Author(s):  
Bassem A Abdullah ◽  
Akmal A Younis ◽  
Nigel M John
Keyword(s):  
State Of The Art ◽  
Automatic Segmentation ◽  
Brain Magnetic Resonance Imaging ◽  
The Other ◽  
Support Vector ◽  
Textural Features ◽  
Lesion Segmentation ◽  
Resonance Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
A New Technique

In this paper, a new technique is proposed for automatic segmentation of multiple sclerosis (MS) lesions from brain magnetic resonance imaging (MRI) data. The technique uses a trained support vector machine (SVM) to discriminate between the blocks in regions of MS lesions and the blocks in non-MS lesion regions mainly based on the textural features with aid of the other features. The classification is done on each of the axial, sagittal and coronal sectional brain view independently and the resultant segmentations are aggregated to provide more accurate output segmentation. The main contribution of the proposed technique described in this paper is the use of textural features to detect MS lesions in a fully automated approach that does not rely on manually delineating the MS lesions. In addition, the technique introduces the concept of the multi-sectional view segmentation to produce verified segmentation. The proposed textural-based SVM technique was evaluated using three simulated datasets and more than fifty real MRI datasets. The results were compared with state of the art methods. The obtained results indicate that the proposed method would be viable for use in clinical practice for the detection of MS lesions in MRI.

scholarly journals EEG Patterns in Patients with Prader-Willi Syndrome

2021 ◽  
Author(s):  
Maurizio Elia ◽  
Irene Rutigliano ◽  
Michele Sacco ◽  
Simona Madeo ◽  
Malgorzata Wasniewska ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Brain Magnetic Resonance Imaging ◽  
The Other ◽  
Prader Willi Syndrome ◽  
Resonance Imaging ◽  
Clinical Genetic ◽  
Behavioral Disturbances ◽  
Neuroimaging Data ◽  
Interictal Eeg ◽  
Magnetic Resonance Imaging Mri

Abstract Prader-Willi syndrome (PWS) is a rare disease determined by the loss of the paternal copy of the 15q11-q13 region, characterized by hypotonia, hyperphagia and obesity, short stature, hypogonadism, craniofacial dysmorphisms, cognitive and behavioral disturbances. The aims of this retrospective study were to analyze interictal EEG findings in a group of PWS patients and to correlate them with genetic, clinical and neuroimaging data. Demographic, clinical, genetic, EEG, and neuroimaging data about seventy-four patients were collected. Associations between the presence of EEG paroxysmal abnormalities, genotype, clinical and neuroimaging features were investigated. Four patients (5.4%) presented a drug-sensitive epilepsy. Interictal EEG paroxysmal abnormalities, focal or multifocal, were present in 25.7% of the cases, and normalization of EEG occurred in about 25% of the cases. In 63.2% of the cases paroxysmal abnormalities were localized over the middle-posterior regions bilaterally. Brain magnetic resonance imaging (MRI) was performed in 39 patients (abnormal in 59%). No relevant associations were found between EEG paroxysmal abnormalities and all the other variables considered. Interictal EEG paroxysmal abnormalities, in particular with a bilateral middle-posterior localization, could represent an important neurological feature of PWS not associated with genotype, cognitive or behavior endophenotypes, MRI anomalies, or prognosis.

scholarly journals EEG Patterns in Patients with Prader–Willi Syndrome

2021 ◽  
Vol 11 (8) ◽  
pp. 1045
Author(s):  
Maurizio Elia ◽  
Irene Rutigliano ◽  
Michele Sacco ◽  
Simona F. Madeo ◽  
Malgorzata Wasniewska ◽  
...  
Keyword(s):  
Brain Magnetic Resonance Imaging ◽  
The Other ◽  
Prader Willi Syndrome ◽  
Resonance Imaging ◽  
Clinical Genetic ◽  
Behavioral Disturbances ◽  
Eeg Abnormalities ◽  
Neuroimaging Data ◽  
Interictal Eeg ◽  
Magnetic Resonance Imaging Mri

Prader–Willi syndrome (PWS) is a rare disease determined by the loss of the paternal copy of the 15q11-q13 region, and it is characterized by hypotonia, hyperphagia, obesity, short stature, hypogonadism, craniofacial dysmorphisms, and cognitive and behavioral disturbances. The aims of this retrospective study were to analyze interictal EEG findings in a group of PWS patients and to correlate them with genetic, clinical, and neuroimaging data. The demographic, clinical, genetic, EEG, and neuroimaging data of seventy-four patients were collected. Associations among the presence of paroxysmal EEG abnormalities, genotype, and clinical and neuroimaging features were investigated. Four patients (5.4%) presented drug-sensitive epilepsy. Interictal paroxysmal EEG abnormalities—focal or multifocal—were present in 25.7% of the cases, and the normalization of the EEG occurred in about 25% of the cases. In 63.2% of the cases, the paroxysmal abnormalities were bilaterally localized over the middle–posterior regions. Brain magnetic resonance imaging (MRI) was performed on 39 patients (abnormal in 59%). No relevant associations were found between paroxysmal EEG abnormalities and all of the other variables considered. Interictal paroxysmal EEG abnormalities—in particular, with a bilateral middle–posterior localization—could represent an important neurological feature of PWS that is not associated with genotype, cognitive or behavioral endophenotypes, MRI anomalies, or prognosis.

scholarly journals Identifying a Common Functional Framework for Apathy Large-Scale Brain Network

2021 ◽  
Vol 11 (7) ◽  
pp. 679
Author(s):  
Vincenzo Alfano ◽  
Mariachiara Longarzo ◽  
Giulia Mele ◽  
Marcello Esposito ◽  
Marco Aiello ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Magnetic Resonance Imaging ◽  
Brain Network ◽  
Neural Pathways ◽  
Resonance Imaging ◽  
Daily Life Activities ◽  
Functional Differences ◽  
Central Gyrus ◽  
Magnetic Resonance Imaging Mri ◽  
Disease Specific

Apathy is a neuropsychiatric condition characterized by reduced motivation, initiative, and interest in daily life activities, and it is commonly reported in several neurodegenerative disorders. The study aims to investigate large-scale brain networks involved in apathy syndrome in patients with frontotemporal dementia (FTD) and Parkinson’s disease (PD) compared to a group of healthy controls (HC). The study sample includes a total of 60 subjects: 20 apathetic FTD and PD patients, 20 non apathetic FTD and PD patients, and 20 HC matched for age. Two disease-specific apathy-evaluation scales were used to measure the presence of apathy in FTD and PD patients; in the same day, a 3T brain magnetic resonance imaging (MRI) with structural and resting-state functional (fMRI) sequences was acquired. Differences in functional connectivity (FC) were assessed between apathetic and non-apathetic patients with and without primary clinical diagnosis revealed, using a whole-brain, seed-to-seed approach. A significant hypoconnectivity between apathetic patients (both FTD and PD) and HC was detected between left planum polare and both right pre- or post-central gyrus. Finally, to investigate whether such neural alterations were due to the underlying neurodegenerative pathology, we replicated the analysis by considering two independent patients’ samples (i.e., non-apathetic PD and FTD). In these groups, functional differences were no longer detected. These alterations may subtend the involvement of neural pathways implicated in a specific reduction of information/elaboration processing and motor outcome in apathetic patients.

Epilepsy in Propionic Acidemia: Case Series of 14 Saudi Patients

2018 ◽  
Vol 33 (11) ◽  
pp. 713-717 ◽  
Author(s):  
Afnan AlGhamdi ◽  
Muhammad Talal Alrifai ◽  
Abdullah I. Al Hammad ◽  
Fuad Al Mutairi ◽  
Abdulrahman Alswaid ◽  
...  
Keyword(s):  
Autosomal Recessive ◽  
Case Series ◽  
Brain Magnetic Resonance Imaging ◽  
Propionic Acidemia ◽  
Resonance Imaging ◽  
Mri Findings ◽  
Epileptiform Discharges ◽  
Magnetic Resonance Imaging Mri ◽  
Autosomal Recessive Manner ◽  
Delayed Myelination

Propionic acidemia is an inborn error of metabolism that is inherited in an autosomal recessive manner. It is characterized by a deficient propionyl-CoA carboxylase due to mutations in either of its beta or alpha subunits. In the literature, there is a clear association between propionic acidemia and epilepsy. In this cohort, we retrospectively reviewed the data of 14 propionic acidemia patients in Saudi Arabia and compared the findings to those of former studies. Six of the 14 (43%) patients developed epileptic seizure, mainly focal seizures. All patients were responsive to conventional antiepileptic drugs as their seizures are controlled. The predominant electroencephalographic (EEG) findings were diffuse slowing in 43% and multifocal epileptiform discharges in 14% of the patients. In 1 patient, burst suppression pattern was detected, a pattern never before reported in patients with propionic acidemia. Brain magnetic resonance imaging (MRI) findings mainly consisted of signal changes of the basal ganglia (36%), generalized brain atrophy (43%), and delayed myelination (43%).The most common genotype in our series is the homozygous missense mutation in the PCCA gene (c.425G>A; p. Gly142Asp). However, there is no clear genotype–seizure correlation. We conclude that seizure is not an uncommon finding in patients with propionic acidemia and not difficult to control. Additional studies are needed to further elaborate on genotype–seizure correlation.

scholarly journals Can we evaluate cranial aneurysms on conventional brain magnetic resonance imaging?

2016 ◽  
Vol 7 (01) ◽  
pp. 83-86 ◽  
Author(s):  
Emine Caliskan ◽  
Yeliz Pekcevik ◽  
Adnan Kaya
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Characteristic Curve ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Kappa Statistics ◽  
Resonance Imaging ◽  
Vascular Structures ◽  
Magnetic Resonance Imaging Mri ◽  
Age Range

ABSTRACT Purpose: To evaluate the contribution of conventional brain magnetic resonance imaging (MRI) for the determination of intracranial aneurysms. Materials and Methods: Brain MRI and computed tomography angiography (CTA) of 45 patients (29 women and 16 men; age range, 32–80 years) with aneurysm were analyzed. A comparison was made between brain MRI and CTA based on size and presence of aneurysm. The comparisons between MRI and CTA were investigated through Bland-Altman graphics, receiver operating characteristic curve, and Kappa statistics. Results: Fifty-seven aneurysms were evaluated. Forty-five percent of 57 aneurysms on CTA were detected on conventional brain MRI. A significant correlation was found between CTA and brain MRI in the diagnosis of aneurysm (P < 0.05). In an analysis of the size measurement, a significant correlation was observed between CTA and brain MRI. Seventy-seven percent of aneurysms <4 mm was not detected and the efficiency of MRI in the detection of aneurysms <4 mm was found to be low. Conclusion: Aneurysms can also be appreciated on conventional brain MRI, and vascular structures should be reviewed carefully while analyzing brain MRI.

The potential of support vector machine as the diagnostic tool for schizophrenia: A systematic literature review of neuroimaging studies

2011 ◽  
Vol 26 (S2) ◽  
pp. 1363-1363 ◽  
Author(s):  
M.P. Collins ◽  
S.E. Pape
Keyword(s):  
Support Vector Machine ◽  
Diagnostic Tool ◽  
Literature Search ◽  
Structural Mri ◽  
Support Vector ◽  
Systematic Literature Search ◽  
Resonance Imaging ◽  
Pubmed Database ◽  
Magnetic Resonance Imaging Mri ◽  
The Individual

IntroductionSchizophrenia is a relatively common chronic psychotic mental illness, which usually continues throughout life. Current diagnosis is based on a set of psychiatrist-applied diagnostic criteria. There can be considerable differences between diagnostic classification based upon either the set of criteria used, or the individual who applies the criteria. For this reason, the development of an objective test to inform the diagnosis could be highly beneficial.ObjectivesTo assess the use of Support Vector Machine (SVM) as a potential diagnostic tool for schizophrenia, with a particular focus on the application of SVM to Magnetic Resonance Imaging (MRI) data.AimsTo show the use of SVM on MRI data to be a potentially viable diagnostic test.MethodA systematic literature search was carried out using the PubMed database, Web of Knowledge as well as Google Scholar. This search was conducted using the terms ‘Schizophrenia’, ‘SVM’/‘Support Vector Machine’ and ‘MRI/fMRI’. This was followed by the application of criteria relating to relevance to the desired search topic (as assesed by the author). Ten publications were identified as relevant.ResultsResults showed strong evidence that the application of SVM to MRI data can reliably differentiate between patients with schizophrenia and healthy controls.ConclusionsThe results indicate that using SVM to analyse MRI data can be reliably used to identify schizophrenia, although there is some variability between the results produced. The potential of SVM in application to fMRI (as opposed to structural MRI) data is yet to be fully explored.

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