Study on the application of MRF and the D-S theory to image segmentation of the human brain and quantitative analysis of the brain tissue

2012 ◽  
Author(s):  
Yihong Guan ◽  
Yatao Luo ◽  
Tao Yang ◽  
Lei Qiu ◽  
Junchang Li
Keyword(s):  
Image Segmentation ◽  
Quantitative Analysis ◽  
Human Brain ◽  
Brain Tissue ◽  
The Brain

scholarly journals Scatterometry Measurements With Scattered Light Imaging Enable New Insights Into the Nerve Fiber Architecture of the Brain

2021 ◽  
Vol 15 ◽  
Author(s):  
Miriam Menzel ◽  
Marouan Ritzkowski ◽  
Jan A. Reuter ◽  
David Gräßel ◽  
Katrin Amunts ◽  
...  
Keyword(s):  
Human Brain ◽  
Nerve Fiber ◽  
Brain Tissue ◽  
Scattered Light ◽  
Polar Angle ◽  
Nerve Fibers ◽  
Fiber Architecture ◽  
Whole Brain ◽  
Tissue Samples ◽  
The Brain

The correct reconstruction of individual (crossing) nerve fibers is a prerequisite when constructing a detailed network model of the brain. The recently developed technique Scattered Light Imaging (SLI) allows the reconstruction of crossing nerve fiber pathways in whole brain tissue samples with micrometer resolution: the individual fiber orientations are determined by illuminating unstained histological brain sections from different directions, measuring the transmitted scattered light under normal incidence, and studying the light intensity profiles of each pixel in the resulting image series. So far, SLI measurements were performed with a fixed polar angle of illumination and a small number of illumination directions, providing only an estimate of the nerve fiber directions and limited information about the underlying tissue structure. Here, we use a display with individually controllable light-emitting diodes to measure the full distribution of scattered light behind the sample (scattering pattern) for each image pixel at once, enabling scatterometry measurements of whole brain tissue samples. We compare our results to coherent Fourier scatterometry (raster-scanning the sample with a non-focused laser beam) and previous SLI measurements with fixed polar angle of illumination, using sections from a vervet monkey brain and human optic tracts. Finally, we present SLI scatterometry measurements of a human brain section with 3 μm in-plane resolution, demonstrating that the technique is a powerful approach to gain new insights into the nerve fiber architecture of the human brain.

scholarly journals Spontaneous glioma-induced seizures recorded in a living human brain tissue preparation

2019 ◽  
Vol 21 (Supplement_4) ◽  
pp. iv16-iv16
Author(s):  
Alastair Kirby ◽  
Jose Pedro Lavrador ◽  
Christian Brogna ◽  
Francesco Vergani ◽  
Bassel Zebian ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Tissue ◽  
Aminolevulinic Acid ◽  
Brain Slices ◽  
Low Grade ◽  
Tissue Preparation ◽  
Spontaneous Seizure ◽  
Human Brain Tissue ◽  
Who Grade ◽  
The Brain

Abstract Gliomas often present clinically with seizures. Tumour-associated seizures can be difficult to control with medication. A deeper understanding of the cellular mechanisms underlying tumour-associated seizures would provide a basis for developing new treatments. Here, we investigate epileptic discharges in peritumoral cortex using living human brain tissue donated by people having a craniotomy for glioma resection (REC approval, 18/SW/002). The brain tissue was cut into thin slices, which preserved the architecture of the glioma and the adjacent healthy brain. The brain slices were incubated in 5-aminolevulinic acid to make the glioma cells fluorescent. This enabled us to make electrophysiological recordings of brain activity across the boundary between glioma and brain. We recorded from brain slices of 5 participants with glioblastoma and 4 participants with oligodendroglioma (WHO grade II – III). Spontaneous “seizure-like” discharges were recorded in brain slices from 5/8 participants (3 GBM, 2 oligodendroglioma) who reported seizures and from one participant (GBM) who had not had any clinical seizures. Further analysis of the seizure-like discharges revealed that they could be subdivided into two distinct types based on the major frequencies in the discharge. We concluded that human brain slices from people with either a low-grade or a high-grade glioma can generate spontaneous seizure-like discharges. The living human brain tissue preparation gives us a platform to study the mechanisms of tumour-associated seizures and how abnormal neural activity affects glioma growth.

scholarly journals An active contour model for brain magnetic resonance image segmentation based on multiple descriptors

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141878341 ◽  
Author(s):  
Chen Hong ◽  
Yu Xiaosheng ◽  
Wu Chengdong ◽  
Wu Jiahui
Keyword(s):  
Image Segmentation ◽  
Magnetic Resonance ◽  
Brain Tissue ◽  
Magnetic Resonance Image ◽  
Active Contour ◽  
Active Contour Model ◽  
Full Description ◽  
Contour Model ◽  
Brain Magnetic Resonance Image ◽  
The Brain

With the increasing use of surgical robots, robust and accurate segmentation techniques for brain tissue in the brain magnetic resonance image are needed to be embedded in the robot vision module. However, the brain magnetic resonance image segmentation results are often unsatisfactory because of noise and intensity inhomogeneity. To obtain accurate segmentation of brain tissue, one new multiphase active contour model, which is based on multiple descriptors mean, variance, and the local entropy, is proposed in this study. The model can bring about a more full description of local intensity distribution. Also, the entropy is introduced to improve the performance of robustness to noise of the algorithm. The segmentation and bias correction for brain magnetic resonance image can be simultaneously incorporated by introducing the bias factor in the proposed approach. At last, three experiments are carried out to test the performance of the method. The results in the experiments show that method proposed in this study performed better than most current methods in regard to accuracy and robustness. In addition, the bias-corrected images obtained by proposed method have better visual effect.

scholarly journals A Novel Brain MRI Image Segmentation Method Using an Improved Multi-View Fuzzy c-Means Clustering Algorithm

2021 ◽  
Vol 15 ◽  
Author(s):  
Lei Hua ◽  
Yi Gu ◽  
Xiaoqing Gu ◽  
Jing Xue ◽  
Tongguang Ni
Keyword(s):  
Image Segmentation ◽  
Brain Tissue ◽  
Adaptive Learning ◽  
Clustering Algorithm ◽  
Brain Mri ◽  
Segmentation Method ◽  
Learning Mechanism ◽  
Fcm Algorithm ◽  
The Brain ◽  
Mri Image

Background: The brain magnetic resonance imaging (MRI) image segmentation method mainly refers to the division of brain tissue, which can be divided into tissue parts such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). The segmentation results can provide a basis for medical image registration, 3D reconstruction, and visualization. Generally, MRI images have defects such as partial volume effects, uneven grayscale, and noise. Therefore, in practical applications, the segmentation of brain MRI images has difficulty obtaining high accuracy.Materials and Methods: The fuzzy clustering algorithm establishes the expression of the uncertainty of the sample category and can describe the ambiguity brought by the partial volume effect to the brain MRI image, so it is very suitable for brain MRI image segmentation (B-MRI-IS). The classic fuzzy c-means (FCM) algorithm is extremely sensitive to noise and offset fields. If the algorithm is used directly to segment the brain MRI image, the ideal segmentation result cannot be obtained. Accordingly, considering the defects of MRI medical images, this study uses an improved multiview FCM clustering algorithm (IMV-FCM) to improve the algorithm’s segmentation accuracy of brain images. IMV-FCM uses a view weight adaptive learning mechanism so that each view obtains the optimal weight according to its cluster contribution. The final division result is obtained through the view ensemble method. Under the view weight adaptive learning mechanism, the coordination between various views is more flexible, and each view can be adaptively learned to achieve better clustering effects.Results: The segmentation results of a large number of brain MRI images show that IMV-FCM has better segmentation performance and can accurately segment brain tissue. Compared with several related clustering algorithms, the IMV-FCM algorithm has better adaptability and better clustering performance.

scholarly journals P11.49 An electrophysiological signature of glioma infiltration in the ex vivo human brain

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii54-iii54
Author(s):  
A J Kirby ◽  
J P Lavrador ◽  
C Brogna ◽  
F Vergani ◽  
C Chandler ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Tissue ◽  
Brain Slices ◽  
Glioma Cells ◽  
Low Grade ◽  
Tissue Preparation ◽  
High Grade ◽  
Spontaneous Seizure ◽  
Human Brain Tissue ◽  
The Brain

Abstract BACKGROUND Invading glioma cells affect the physiological function of the peritumoural cortex. This may manifest clinically as seizures. Here, we investigate the effect the invading glioma cells on the electrophysiological signalling of the peritumoral cortex using living human brain tissue donated by people having a craniotomy for glioma resection (REC approval, 18/SW/002). MATERIAL AND METHODS The brain tissue was cut into thin slices, which preserved the architecture of the glioma and the adjacent healthy brain. The brain slices were incubated in 5-aminolevulinic acid to make the glioma cells fluorescent. We observed 5-ALA induced fluorescence in both low-grade and high-grade gliomas. This enabled us to make electrophysiological recordings of brain activity across the boundary between glioma and brain. RESULTS We recorded from brain slices of 5 participants with glioblastoma and 4 participants with oligodendroglioma (WHO grade II - III). Spontaneous “seizure-like” discharges were recorded in brain slices from 5/8 participants (3 GBM, 2 oligodendroglioma) who reported seizures and from one participant (GBM) who had not had any clinical seizures. Further analysis of the electrical discharges revealed that they could be subdivided into two distinct types based on the major frequencies in the discharge. CONCLUSION We concluded that human brain slices from people with either a low-grade or a high-grade glioma can generate spontaneous seizure-like discharges. This electrophysiological signature will be compared to infiltration and grade of the glioma cells in the donated sample. The living human brain tissue preparation gives us a platform to study the mechanisms of tumour-associated seizures and how abnormal neural activity affects glioma growth.

Bio-Degradable Glass for Neural Probe Application

2013 ◽  
Vol 740 ◽  
pp. 555-559 ◽  
Author(s):  
Rui Qi Lim ◽  
Kwan Ling Tan ◽  
Wei Guo Chen ◽  
Mink Yu Je ◽  
Tack Boon Yee ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Tissue ◽  
Brain Neuron ◽  
Tissue Movement ◽  
Neural Probe ◽  
The Brain

This work presents a bio-degradable glass probes and its biocompatibility assessment for neural applications. The probes can be implanted into different sites of the human brain for recording and stimulating purposes. Current existing neural probe address the probe stiffness requirement for the penetration of brain tissue. However, this requirement normally resulted in the rigidity of the probe which is non-compatible with the brain tissue movement for long term implantation. The brain neuron cells will be damaged by too rigid probe substrate. In order to address this issue, bio-degradable glass probes having sufficient stiffness for a smooth brain insertion as well as ability to degrade after implantation; leaving behind the flexible circuitry substrate was being explored. The biodegradability of the proposed probe was evaluated.

scholarly journals Genome Sequences of Novel Torque Teno Viruses Identified in Human Brain Tissue

2020 ◽  
Vol 9 (37) ◽  
Author(s):  
Simona Kraberger ◽  
Diego Mastroeni ◽  
Elaine Delvaux ◽  
Arvind Varsani
Keyword(s):  
Human Brain ◽  
Brain Tissue ◽  
Complete Genome ◽  
Open Reading Frame ◽  
Human Brain Tissue ◽  
Genome Sequences ◽  
Reading Frame ◽  
The Brain ◽  
Open Reading Frame 1

ABSTRACT Complete genome sequences of two novel torque teno viruses (TTVs) were identified in human brain tissue. These sequences are 3,245 nucleotides (nt) and 2,900 nt long and share 68% and 72% open reading frame 1 (ORF1) identity, respectively, with other human TTVs. This report extends the identification of TTV sequences in the brain.

The right way, the wrong way, and the army way: A dendritic parable

1997 ◽  
Vol 20 (4) ◽  
pp. 575-575
Author(s):  
Arnold B. Scheibel
Keyword(s):  
Human Brain ◽  
Brain Tissue ◽  
Structural Studies ◽  
Human Brain Tissue ◽  
Tissue Mass ◽  
The Right ◽  
The Brain

We suggest that neither selectionism nor constructivism alone are responsible for learning-based changes in the brain. On the basis of quantitative structural studies of human brain tissue it has been possible to find evidence of both increase and decrease in tissue mass at synaptic and dendritic levels. It would appear that both processes are involved in the course of learning-dependent changes.

scholarly journals Identification of the ZEB2 gene as a potential target for epilepsy therapy and the association between rs10496964 and ZEB2 expression

2020 ◽  
Vol 48 (12) ◽  
pp. 030006052098052
Author(s):  
Shitao Wang ◽  
Dan Wang ◽  
Xuemei Cai ◽  
Qian Wu ◽  
Yanbing Han
Keyword(s):  
Human Brain ◽  
Brain Tissue ◽  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Human Brain Tissue ◽  
Protein Protein Interaction ◽  
Epilepsy Therapy ◽  
The Brain ◽  
Zeb2 Expression

Objective An association between the rs10496964 polymorphism and the ZEB2 gene has not yet been reported, and the role of ZEB2 in epilepsy therapy is also unclear. The aims of this research were to evaluate the role of ZEB2 in the therapy of epilepsy and to explore the association between rs10496964 and ZEB2 expression. Methods We used the expression quantitative trait loci (eQTL) dataset resource from the Brain eQTL Almanac to evaluate the association between rs10496964 and ZEB2 expression in human brain tissue. Pathway and process enrichment analysis, protein–protein interaction analysis, and PhosphoSitePlus® analysis were then performed to further evaluate the role of ZEB2 in the therapy of epilepsy. Results The rs10496964 polymorphism was found to regulate the expression of ZEB2 in human brain tissue. The ZEB2 protein interacts with the targets of approved antiepileptic drugs, and a post-translational acetylation modification of ZEB2 was associated with an epilepsy drug therapy. Conclusion Our findings suggest that ZEB2 may be involved in the therapy of epilepsy, and rs10496964 regulates ZEB2 expression in human brain tissue.

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