Unsupervised Segmentation of Brain Tissues using Multiphase Level Sets on Multiple MRI Sequences

2011 ◽  
Author(s):  
Elisa Veronese ◽  
Enea Poletti ◽  
Massimiliano Calabrese ◽  
Alessandra Bertoldo ◽  
Enrico Grisan
Keyword(s):  
Level Sets ◽  
Unsupervised Segmentation ◽  
Mri Sequences ◽  
Brain Tissues

scholarly journals A fully automatic unsupervised segmentation framework for the brain tissues in MR images

2014 ◽  
Author(s):  
Qaiser Mahmood ◽  
Artur Chodorowski ◽  
Babak Ehteshami Bejnordi ◽  
Mikael Persson
Keyword(s):  
Mr Images ◽  
Unsupervised Segmentation ◽  
Fully Automatic ◽  
Segmentation Framework ◽  
The Brain ◽  
Brain Tissues

Unsupervised segmentation of the vocal tract from real-time MRI sequences

2015 ◽  
Vol 33 (1) ◽  
pp. 25-46 ◽  
Author(s):  
Samuel Silva ◽  
António Teixeira
Keyword(s):  
Real Time ◽  
Vocal Tract ◽  
Unsupervised Segmentation ◽  
Mri Sequences

Characterization of Ischemic Stroke in CT Images using Image Processing

2017 ◽  
Vol 7 (9) ◽  
pp. 18
Author(s):  
Amal Alzain ◽  
Suhaib Alameen ◽  
Rani Elmaki ◽  
Mohamed E. M. Gar-Elnabi
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Classification Accuracy ◽  
Ct Images ◽  
Gray Level ◽  
Level Variation ◽  
Interactive Data ◽  
The Brain ◽  
Brain Tissues

This study concern to characterize the brain tissues to ischemic stroke, gray matter, white matter and CSF using texture analysisto extract classification features from CT images. The First Order Statistic techniques included sevenfeatures. To find the gray level variation in CT images it complements the FOS features extracted from CT images withgray level in pixels and estimate the variation of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level of images. The results show that the Gray Level variation and   features give classification accuracy of ischemic stroke 97.6%, gray matter95.2%, white matter 97.3% and the CSF classification accuracy 98.0%. The overall classification accuracy of brain tissues 97.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate brain tissues names.

Effect of alkaloid extracted from Huperzia phlegmaria on cognitive deficits scopolamine-induced in mice

2020 ◽  
Vol 16 ◽  
Author(s):  
Dang Kim Thu ◽  
Dao Thi Vui ◽  
Nguyen Thi Ngoc Huyen ◽  
Nguyen Thi Thanh Binh ◽  
Nguyen Thi Huyen ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mouse Brain ◽  
Cognitive Deficits ◽  
Inhibitory Activity ◽  
Water Maze ◽  
Ache Activity ◽  
Y Maze ◽  
Ache Inhibitory Activity ◽  
Kinetic Inhibition ◽  
Brain Tissues

Background: Huperzia phlegmaria has been used for the treatment of neurological disorder. Alkaloids are main bioactive compounds found in Huperzia phlegmaria. We aimed to investigate the acetylcholinesterase (AChE) inhibitory activity in vitro of Huperzia phlegmaria alkaloid extract (HpAE) and protective effects on mice which were induced cognitive deficits by scopolamine. Methods: AChE inhibitory activity and kinetic inhibition mechanism was investigated by Ellman's assay. Mice were administrated orally HpAE (30 mg/kg and 60 mg/kg) for fourteen days, and injected scopolamine at a dose of 1 mg/kg intraperitoneally for four days to induce cognitive impairment. The Y-maze and the Morris water maze were used for evaluating the memory behaviors. Acetylcholine (ACh) levels and AChE activity were measured in brain tissue. Glutathione peroxidase (GPx), superoxide dismutase (SOD) activities, and malondialdehyde (MDA) groups were also evaluated in the mouse brain tissues. Results: Our data showed that HpAE had the strong AChE inhibitory activity with an IC50 value of 5.12 ± 0.48 μg/mL in a concentration-dependent manner. Kinetic inhibition analysis demonstrated that HpPAE inhibited AChE followed the mixed inhibition type with Ki (representing the affinity of the enzyme and inhibitor) was 4.37 ± 0.35 µg/mL. Scopolamine induced the cognitive impairment in Morris Water Maze and Y-maze test along with reduced brain levels of ACh and antioxidant enzyme and increased AChE activity in mouse brain tissues. Treatment with HpAE at both dose (30 mg/kg and 60 mg/kg) decreased the SCP-induced cognitive impairment in both behavioral tests along with decreased acetylcholinesterase activity and MDA level, and increased ACh level and antioxidant enzyme in mouse brain tissues. Conclusion: Our results suggested that the HpAE at both dose (30 mg/kg and 60 mg/kg) may be used for prevent and treatment of Alzheimer’s disease.

Perfect level sets in many directions

1986 ◽  
Vol 12 (1) ◽  
pp. 176
Author(s):  
Malý
Keyword(s):  
Level Sets

LEVEL SETS OF A TYPICAL C n FUNCTION

1998 ◽  
Vol 24 (1) ◽  
pp. 83
Author(s):  
Darji ◽  
Morayne
Keyword(s):  
Level Sets

scholarly journals The Effect of Heterogenous Subregions in Glioblastomas on Survival Stratification: A Radiomics Analysis Using the Multimodality MRI

2021 ◽  
Vol 20 ◽  
pp. 153303382110330
Author(s):  
Lulu Yin ◽  
Yan Liu ◽  
Xi Zhang ◽  
Hongbing Lu ◽  
Yang Liu
Keyword(s):  
Poor Prognosis ◽  
Intratumor Heterogeneity ◽  
Short Term ◽  
Prognostic Information ◽  
Manual Delineation ◽  
Flair Sequence ◽  
The Poor ◽  
Contrast Enhanced ◽  
Mri Sequences

Intratumor heterogeneity is partly responsible for the poor prognosis of glioblastoma (GBM) patients. In this study, we aimed to assess the effect of different heterogeneous subregions of GBM on overall survival (OS) stratification. A total of 105 GBM patients were retrospectively enrolled and divided into long-term and short-term OS groups. Four MRI sequences, including contrast-enhanced T1-weighted imaging (T1C), T1, T2, and FLAIR, were collected for each patient. Then, 4 heterogeneous subregions, i.e. the region of entire abnormality (rEA), the regions of contrast-enhanced tumor (rCET), necrosis (rNec) and edema/non-contrast-enhanced tumor (rE/nCET), were manually drawn from the 4 MRI sequences. For each subregion, 50 radiomics features were extracted. The stratification performance of 4 heterogeneous subregions, as well as the performances of 4 MRI sequences, was evaluated both alone and in combination. Our results showed that rEA was superior in stratifying long-and short-term OS. For the 4 MRI sequences used in this study, the FLAIR sequence demonstrated the best performance of survival stratification based on the manual delineation of heterogeneous subregions. Our results suggest that heterogeneous subregions of GBMs contain different prognostic information, which should be considered when investigating survival stratification in patients with GBM.

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