Automatic Registration of MRI Brain

Author(s):  
Piotr Zarychta ◽  
Anna Zarychta-Bargieła
2019 ◽  
Vol 50 (2) ◽  
pp. 98-112 ◽  
Author(s):  
KALYAN KUMAR JENA ◽  
SASMITA MISHRA ◽  
SAROJANANDA MISHRA ◽  
SOURAV KUMAR BHOI ◽  
SOUMYA RANJAN NAYAK

2016 ◽  
Vol 11 (2) ◽  
pp. 114-120 ◽  
Author(s):  
C. Peter Devadoss ◽  
Balasubramanian Sankaragomathi ◽  
Thirugnanasambantham Monica

2020 ◽  
Vol 15 (4) ◽  
pp. 287-299
Author(s):  
Jie Zhang ◽  
Junhong Feng ◽  
Fang-Xiang Wu

Background: : The brain networks can provide us an effective way to analyze brain function and brain disease detection. In brain networks, there exist some import neural unit modules, which contain meaningful biological insights. Objective:: Therefore, we need to find the optimal neural unit modules effectively and efficiently. Method:: In this study, we propose a novel algorithm to find community modules of brain networks by combining Neighbor Index and Discrete Particle Swarm Optimization (DPSO) with dynamic crossover, abbreviated as NIDPSO. The differences between this study and the existing ones lie in that NIDPSO is proposed first to find community modules of brain networks, and dose not need to predefine and preestimate the number of communities in advance. Results: : We generate a neighbor index table to alleviate and eliminate ineffective searches and design a novel coding by which we can determine the community without computing the distances amongst vertices in brain networks. Furthermore, dynamic crossover and mutation operators are designed to modify NIDPSO so as to alleviate the drawback of premature convergence in DPSO. Conclusion: The numerical results performing on several resting-state functional MRI brain networks demonstrate that NIDPSO outperforms or is comparable with other competing methods in terms of modularity, coverage and conductance metrics.


2016 ◽  
Vol 5 (10) ◽  
pp. 4982
Author(s):  
Archana Aher* ◽  
Satish Gore

This study was conducted to determine the clinical evaluation and various etiological factors of secondary seizures in patients admitted to Government Medical College, Nagpur. We evaluated 58 patients of secondary seizures from Dec 2011 to Oct 2013. Secondary seizures were defined as case of seizure with CT (brain) or MRI (brain) abnormality1. Out of 58 cases 35 were males and 23 were females. Mean age of study subjects was 34.85. The commonest presenting feature was generalized tonic clonic convulsions (42 patients) followed by focal seizures (16 patients).  Todd’s palsy was observed in 4 cases. Aura was present in 24 cases. According to CT brain scan the aetiology was – neurocysticercosis (34.48%), post stroke (27.59%), tuberculoma (24.14%). Space occupying lesions(SOLs) were present in 8 patients, out of whom 4 had brain tumour, 2 patients had brain abscess, 1 had hydatid cyst and 1 had metastasis. Majority of lesions were located in frontal region (58.62%), followed by in parietal region (44.83%), in temporal region (25.86%) and in occipital region (13.79 % patients). In our study neurocysticercosis was found to be the commonest cause of secondary seizures. As in a meta-analysis it was found that cysticidal drugs result in better outcome in patients of neurocysticecosis, we recommend that the patients of secondary seizures should be identified for the aetiology and treated at the earliest2.


2018 ◽  
Author(s):  
Mohamed Fleifel ◽  
Rawya Abdelghani ◽  
Mohamed Ameen

BACKGROUND Background: Studying the neurological developmental outcomes and comparing correlations with MRI (Magnetic resonance image) versus the Hammersmith Infant Neurological Examination (HINE) OBJECTIVE Objective: To investigate the non-inferiority of MRI to HINE in infant developmental outcomes METHODS Settings: Hospital settings including pediatrics and neonatal care units Intervention: No medical or surgical intervention is planned, only correlation and extra analyses would take place to standardize the current practice Measurements: HINE, Brain MRI, Brain Ultrasound and developmental outcomes after 12 months RESULTS Results: The observations collected and correlations measured to figure out the reliability of both HINE and MRI in order to figure to what extent can we rely on HINE alone in expecting the developmental outcomes CONCLUSIONS The more reliability would expressed by HINE assessment the accurate expectation of developmental in preterm infants CLINICALTRIAL https://clinicaltrials.gov/ct2/show/NCT03580252


Sign in / Sign up

Export Citation Format

Share Document