scholarly journals Whole-Brain Vasculature Reconstruction at the Single Capillary Level

2017 ◽  
Author(s):  
Antonino Paolo Di Giovanna ◽  
Alessandro Tibo ◽  
Ludovico Silvestri ◽  
Marie Caroline Müllenbroich ◽  
Irene Costantini ◽  
...  
Keyword(s):  
Automatic Segmentation ◽  
Light Sheet ◽  
Best Available Techniques ◽  
Brain Vasculature ◽  
Novel Approach ◽  
Segmentation Algorithms ◽  
Novel Method ◽  
Endogenous Fluorescence ◽  
High Throughput Imaging ◽  
The Brain

ABSTRACTThe distinct organization of the brain’s vascular network ensures that it is adequately supplied with oxygen and nutrients. However, despite this fundamental role, a detailed reconstruction of the brain-wide vasculature at the capillary level remains elusive, due to insufficient image quality using the best available techniques. Here, we demonstrate a novel approach that improves vascular demarcation by combining CLARITY with a vascular staining approach that can fill the entire blood vessel lumen and imaging with light-sheet fluorescence microscopy. This method significantly improves image contrast, particularly in depth, thereby allowing reliable application of automatic segmentation algorithms, which play an increasingly important role in high-throughput imaging of the terabyte-sized datasets now routinely produced. Furthermore, our novel method is compatible with endogenous fluorescence, thus allowing simultaneous investigations of vasculature and genetically targeted neurons. We believe our new method will be valuable for future brain-wide investigations of the capillary network.

Directional Vector-Based Skin Lesion Segmentation — A Novel Approach to Skin Segmentation

2020 ◽  
Vol 20 (03) ◽  
pp. 2050021
Author(s):  
P. Nikesh ◽  
G. Raju
Keyword(s):  
Skin Lesion ◽  
Automatic Segmentation ◽  
High Accuracy ◽  
Lesion Segmentation ◽  
Seed Point ◽  
Skin Segmentation ◽  
Novel Approach ◽  
Segmentation Algorithms ◽  
Computer Aided ◽  
Aided Diagnosis

Efficient skin lesion segmentation algorithms are required for computer aided diagnosis of skin cancer. Several algorithms were proposed for skin lesion segmentation. The existing algorithms are short of achieving ideal performance. In this paper, a novel semi-automatic segmentation algorithm is proposed. The fare concept of the proposed is 8-directional search based on threshold for lesion pixel, starting from a user provided seed point. The proposed approach is tested on 200 images from PH2 and 900 images from ISBI 2016 datasets. In comparison to a chosen set of algorithms, the proposed approach gives high accuracy and specificity values. A significant advantage of the proposed method is the ability to deal with discontinuities in the lesion.

scholarly journals 3D U-Net for Skull Stripping in Brain MRI

2019 ◽  
Vol 9 (3) ◽  
pp. 569 ◽  
Author(s):  
Hyunho Hwang ◽  
Hafiz Zia Ur Rehman ◽  
Sungon Lee
Keyword(s):  
Deep Learning ◽  
Automatic Segmentation ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Brain Extraction ◽  
Skull Stripping ◽  
Segmentation Algorithms ◽  
Magnetic Resonance Imaging Mri ◽  
Deep Learning Network ◽  
The Brain

Skull stripping in brain magnetic resonance imaging (MRI) is an essential step to analyze images of the brain. Although manual segmentation has the highest accuracy, it is a time-consuming task. Therefore, various automatic segmentation algorithms of the brain in MRI have been devised and proposed previously. However, there is still no method that solves the entire brain extraction problem satisfactorily for diverse datasets in a generic and robust way. To address these shortcomings of existing methods, we propose the use of a 3D-UNet for skull stripping in brain MRI. The 3D-UNet was recently proposed and has been widely used for volumetric segmentation in medical images due to its outstanding performance. It is an extended version of the previously proposed 2D-UNet, which is based on a deep learning network, specifically, the convolutional neural network. We evaluated 3D-UNet skull-stripping using a publicly available brain MRI dataset and compared the results with three existing methods (BSE, ROBEX, and Kleesiek’s method; BSE and ROBEX are two conventional methods, and Kleesiek’s method is based on deep learning). The 3D-UNet outperforms two typical methods and shows comparable results with the specific deep learning-based algorithm, exhibiting a mean Dice coefficient of 0.9903, a sensitivity of 0.9853, and a specificity of 0.9953.

Longitudinal Changes in Individual BrainAGE in Healthy Aging, Mild Cognitive Impairment, and Alzheimer’s Disease

GeroPsych ◽  
2012 ◽  
Vol 25 (4) ◽  
pp. 235-245 ◽  
Author(s):  
Katja Franke ◽  
Christian Gaser
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Healthy Aging ◽  
Brain Aging ◽  
Elderly Subjects ◽  
Additional Increase ◽  
Longitudinal Changes ◽  
Novel Method ◽  
The Brain

We recently proposed a novel method that aggregates the multidimensional aging pattern across the brain to a single value. This method proved to provide stable and reliable estimates of brain aging – even across different scanners. While investigating longitudinal changes in BrainAGE in about 400 elderly subjects, we discovered that patients with Alzheimer’s disease and subjects who had converted to AD within 3 years showed accelerated brain atrophy by +6 years at baseline. An additional increase in BrainAGE accumulated to a score of about +9 years during follow-up. Accelerated brain aging was related to prospective cognitive decline and disease severity. In conclusion, the BrainAGE framework indicates discrepancies in brain aging and could thus serve as an indicator for cognitive functioning in the future.

scholarly journals A novel approach to the computation of one-loop three- and four-point functions: I. The real mass case

2019 ◽  
Vol 2019 (11) ◽  
Author(s):  
J Ph Guillet ◽  
E Pilon ◽  
Y Shimizu ◽  
M S Zidi
Keyword(s):  
Building Blocks ◽  
The Real ◽  
Alternative Method ◽  
Novel Approach ◽  
Reduction Methods ◽  
Real Mass ◽  
Novel Method ◽  
Algebraic Reduction ◽  
The One ◽  
Mass Case

Abstract This article is the first of a series of three presenting an alternative method of computing the one-loop scalar integrals. This novel method enjoys a couple of interesting features as compared with the method closely following ’t Hooft and Veltman adopted previously. It directly proceeds in terms of the quantities driving algebraic reduction methods. It applies to the three-point functions and, in a similar way, to the four-point functions. It also extends to complex masses without much complication. Lastly, it extends to kinematics more general than that of the physical, e.g., collider processes relevant at one loop. This last feature may be useful when considering the application of this method beyond one loop using generalized one-loop integrals as building blocks.

The Good Sower: A Novel Approach to Teaching Sunday School

2021 ◽  
pp. 073989132199312
Author(s):  
Lisa Marie Anderson-Umana
Keyword(s):  
Daily Life ◽  
Sunday School ◽  
School Students ◽  
The Bible ◽  
Novel Approach ◽  
Approach To Teaching ◽  
The Brain

The problems related to Sunday school students not making the connection between Scripture and daily life and a superficial teaching of the Bible compelled the author to create a novel approach to teaching Sunday school called the “Good Sower.” The imagery of a “Good Sower” is used to teach volunteers how to teach the Bible. Based on solid research regarding how the brain learns, it serves as an overlay in conjunction with published curriculum.

scholarly journals Fast, accurate, and reproducible automatic segmentation of the brain in T1-weighted volume MRI data

1999 ◽  
Vol 42 (1) ◽  
pp. 127-135 ◽  
Author(s):  
Louis Lemieux ◽  
Georg Hagemann ◽  
Karsten Krakow ◽  
Friedrich G. Woermann
Keyword(s):  
Automatic Segmentation ◽  
The Brain

scholarly journals Crawling Phagocytes Recruited in the Brain Vasculature after Pertussis Toxin Exposure through IL6, ICAM1 and ITGαM

2011 ◽  
Vol 21 (6) ◽  
pp. 661-671 ◽  
Author(s):  
Jean-François Richard ◽  
Monica Roy ◽  
Julie Audoy-Rémus ◽  
Pierrot Tremblay ◽  
Luc Vallières
Keyword(s):  
Pertussis Toxin ◽  
Brain Vasculature ◽  
Toxin Exposure ◽  
The Brain

Abstract MP17: Upregulating E2F1 Mitigates Senescence-Associated Phenotypes in Cultured Primary Endothelial Cells

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Michael E Maniskas ◽  
Yun-ju Lai ◽  
Sean P Marrelli ◽  
Louise D McCullough ◽  
Jose F Moruno-manchon
Keyword(s):  
Endothelial Cells ◽  
Vascular Endothelial Cells ◽  
Neurovascular Unit ◽  
Glucose Deprivation ◽  
Cerebral Hypoperfusion ◽  
Aged Mouse ◽  
Aged Mice ◽  
Brain Vasculature ◽  
Bilateral Carotid ◽  
The Brain

Vascular contributions to cognitive impairment and dementia (VCID) includes multiple disorders that are identified by cognitive deficits secondary to cerebrovascular pathology. The risk of VCID is higher in people after the age of 70, and, currently, there is no effective treatment. Vascular endothelial cells (VEC) are critical components of the brain vasculature and neurovascular unit and their health is vital to the capacity of the brain vasculature to respond to stressors. However, aged VEC may enter an irreversible replicative-arrest state (senescence), which has been associated with dementia. E2F transcription factor 1 (E2F1) regulates cell cycle progression and DNA damage repair. Importantly, E2F1 deficiency is associated with cell senescence. We hypothesized that E2F1 downregulation contributes to senescence in the cerebral endothelium during aging. We used cultured primary VEC from young (4-months old, mo) and aged (18-mo) male and female mice for RNA sequencing, plasmid-based gene delivery, high-resolution microscopy, and (4-, 12-, and 18-mo) mice of the bilateral carotid artery stenosis (BCAS) model, which produces chronic cerebral hypoperfusion and recapitulates some of the features seen in patients with VCID. We found that overexpression of E2F1 reduced the levels of senescence-associated phenotypes in cultured VEC from young mice that were exposed to oxygen and glucose deprivation (p<0.001), which induces endothelial senescence. Our RNA seq data showed that the expression of E2f1 was reduced (~40%) in cultured primary VEC from aged mouse brains compared with young cells (p<0.001). E2F1 levels were reduced in the brains of aged mice. Interestingly, we found sex differences in E2F1 levels, with less protein levels (~30%) in males vs females (p<0.05), independently of age. Also, aged BCAS mice (1 month after surgery) had more severe senescence phenotypes, reduced cerebral blood flow, and worse memory deficits compared with control mice (p<0.05). The effect of BCAS was more prominent in aged mice compared with younger (4- and 12-mo) mice. In conclusion , our study identifies E2F1 as a potential regulator of endothelial senescence in mice and highlights the contribution of aging as an important factor in losing endothelial resilience.

Novel approach for automatic segmentation of LV endocardium via SPCNN

2017 ◽  
Author(s):  
Yurun Ma ◽  
Deyuan Wang ◽  
Yide Ma ◽  
Ruoming Lei ◽  
Kemin Wang
Keyword(s):  
Automatic Segmentation ◽  
Novel Approach
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