scholarly journals Optical Imaging in Brainsmatics

Photonics ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 98 ◽  
Author(s):  
Shi ◽  
Guan ◽  
Chen ◽  
Luo
Keyword(s):  
Optical Imaging ◽  
Single Neuron ◽  
Spatial Information ◽  
Imaging Techniques ◽  
Cellular Level ◽  
Brain Connectome ◽  
Level Information ◽  
World Brain ◽  
Development Objectives ◽  
The Brain

When neuroscience’s focus moves from molecular and cellular level to systems level, information technology mixes in and cultivates a new branch neuroinformatics. Especially under the investments of brain initiatives all around the world, brain atlases and connectomics are identified as the substructure to understand the brain. We think it is time to call for a potential interdisciplinary subject, brainsmatics, referring to brain-wide spatial informatics science and emphasizing on precise positioning information affiliated to brain-wide connectome, genome, proteome, transcriptome, metabolome, etc. Brainsmatics methodology includes tracing, surveying, visualizing, and analyzing brain-wide spatial information. Among all imaging techniques, optical imaging is the most appropriate solution to achieve whole-brain connectome in consistent single-neuron resolution. This review aims to introduce contributions of optical imaging to brainsmatics studies, especially the major strategies applied in tracing and surveying processes. After discussions on the state-of-the-art technology, the development objectives of optical imaging in brainsmatics field are suggested. We call for a global contribution to the brainsmatics field from all related communities such as neuroscientists, biologists, engineers, programmers, chemists, mathematicians, physicists, clinicians, pharmacists, etc. As the leading approach, optical imaging will, in turn, benefit from the prosperous development of brainsmatics.

scholarly journals Optical Imaging of Beta-Amyloid Plaques in Alzheimer’s Disease

Biosensors ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 255
Author(s):  
Ziyi Luo ◽  
Hao Xu ◽  
Liwei Liu ◽  
Tymish Y. Ohulchanskyy ◽  
Junle Qu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Optical Imaging ◽  
Imaging Techniques ◽  
High Sensitivity ◽  
Pathological Feature ◽  
Promising Tool ◽  
Abnormal Accumulation ◽  
Accumulation Mechanism ◽  
The Brain

Alzheimer’s disease (AD) is a multifactorial, irreversible, and incurable neurodegenerative disease. The main pathological feature of AD is the deposition of misfolded β-amyloid protein (Aβ) plaques in the brain. The abnormal accumulation of Aβ plaques leads to the loss of some neuron functions, further causing the neuron entanglement and the corresponding functional damage, which has a great impact on memory and cognitive functions. Hence, studying the accumulation mechanism of Aβ in the brain and its effect on other tissues is of great significance for the early diagnosis of AD. The current clinical studies of Aβ accumulation mainly rely on medical imaging techniques, which have some deficiencies in sensitivity and specificity. Optical imaging has recently become a research hotspot in the medical field and clinical applications, manifesting noninvasiveness, high sensitivity, absence of ionizing radiation, high contrast, and spatial resolution. Moreover, it is now emerging as a promising tool for the diagnosis and study of Aβ buildup. This review focuses on the application of the optical imaging technique for the determination of Aβ plaques in AD research. In addition, recent advances and key operational applications are discussed.

scholarly journals Retinal correlates of neurological disorders

2019 ◽  
Vol 10 ◽  
pp. 204062231988220 ◽  
Author(s):  
Timothy E. Yap ◽  
Shiama I. Balendra ◽  
Melanie T. Almonte ◽  
M. Francesca Cordeiro
Keyword(s):  
Imaging Techniques ◽  
Prion Diseases ◽  
High Sensitivity ◽  
Cellular Level ◽  
Correct Treatment ◽  
Optical Media ◽  
Developing Area ◽  
The Brain ◽  
Lateral Sclerosis

Considering the retina as an extension of the brain provides a platform from which to study diseases of the nervous system. Taking advantage of the clear optical media of the eye and ever-increasing resolution of modern imaging techniques, retinal morphology can now be visualized at a cellular level in vivo. This has provided a multitude of possible biomarkers and investigative surrogates that may be used to identify, monitor and study diseases until now limited to the brain. In many neurodegenerative conditions, early diagnosis is often very challenging due to the lack of tests with high sensitivity and specificity, but, once made, opens the door to patients accessing the correct treatment that can potentially improve functional outcomes. Using retinal biomarkers in vivo as an additional diagnostic tool may help overcome the need for invasive tests and histological specimens, and offers the opportunity to longitudinally monitor individuals over time. This review aims to summarise retinal biomarkers associated with a range of neurological conditions including Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS) and prion diseases from a clinical perspective. By comparing their similarities and differences according to primary pathological processes, we hope to show how retinal correlates can aid clinical decisions, and accelerate the study of this rapidly developing area of research.

scholarly journals Neuroanatomical phenotyping of the mouse brain with three-dimensional autofluorescence imaging

2012 ◽  
Vol 44 (15) ◽  
pp. 778-785 ◽  
Author(s):  
Jacqueline A. Gleave ◽  
Michael D. Wong ◽  
Jun Dazai ◽  
Maliha Altaf ◽  
R. Mark Henkelman ◽  
...  
Keyword(s):  
Optical Imaging ◽  
Mouse Brain ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Brain Structures ◽  
Small Scale ◽  
Specimen Preparation ◽  
Normal Brain ◽  
Autofluorescence Imaging ◽  
The Brain

The structural organization of the brain is important for normal brain function and is critical to understand in order to evaluate changes that occur during disease processes. Three-dimensional (3D) imaging of the mouse brain is necessary to appreciate the spatial context of structures within the brain. In addition, the small scale of many brain structures necessitates resolution at the ∼10 μm scale. 3D optical imaging techniques, such as optical projection tomography (OPT), have the ability to image intact large specimens (1 cm3) with ∼5 μm resolution. In this work we assessed the potential of autofluorescence optical imaging methods, and specifically OPT, for phenotyping the mouse brain. We found that both specimen size and fixation methods affected the quality of the OPT image. Based on these findings we developed a specimen preparation method to improve the images. Using this method we assessed the potential of optical imaging for phenotyping. Phenotypic differences between wild-type male and female mice were quantified using computer-automated methods. We found that optical imaging of the endogenous autofluorescence in the mouse brain allows for 3D characterization of neuroanatomy and detailed analysis of brain phenotypes. This will be a powerful tool for understanding mouse models of disease and development and is a technology that fits easily within the workflow of biology and neuroscience labs.

scholarly journals Combining tissue engineering and optical imaging approaches to explore interactions along the neuro-cardiac axis

2020 ◽  
Vol 7 (6) ◽  
pp. 200265 ◽  
Author(s):  
Charalampos Sigalas ◽  
Maegan Cremer ◽  
Annika Winbo ◽  
Samuel J. Bose ◽  
Jesse L. Ashton ◽  
...  
Keyword(s):  
Tissue Engineering ◽  
Optical Imaging ◽  
Imaging Techniques ◽  
Cell Types ◽  
Tissue Level ◽  
Cellular Level ◽  
Optical Recording ◽  
Polymorphic Ventricular Tachycardia ◽  
Cardiac Diseases

Interactions along the neuro-cardiac axis are being explored with regard to their involvement in cardiac diseases, including catecholaminergic polymorphic ventricular tachycardia, hypertension, atrial fibrillation, long QT syndrome and sudden death in epilepsy. Interrogation of the pathophysiology and pathogenesis of neuro-cardiac diseases in animal models present challenges resulting from species differences, phenotypic variation, developmental effects and limited availability of data relevant at both the tissue and cellular level. By contrast, tissue-engineered models containing cardiomyocytes and peripheral sympathetic and parasympathetic neurons afford characterization of cellular- and tissue-level behaviours while maintaining precise control over developmental conditions, cellular genotype and phenotype. Such approaches are uniquely suited to long-term, high-throughput characterization using optical recording techniques with the potential for increased translational benefit compared to more established techniques. Furthermore, tissue-engineered constructs provide an intermediary between whole animal/tissue experiments and in silico models. This paper reviews the advantages of tissue engineering methods of multiple cell types and optical imaging techniques for the characterization of neuro-cardiac diseases.

scholarly journals Post mortem mapping of connectional anatomy for the validation of diffusion MRI

2021 ◽  
Author(s):  
Anastasia Yendiki ◽  
Manisha Aggarwal ◽  
Markus Axer ◽  
Amy FD Howard ◽  
Anne-Marie van Cappellen van Walsum ◽  
...  
Keyword(s):  
Optical Imaging ◽  
Diffusion Mri ◽  
Imaging Techniques ◽  
Post Mortem ◽  
Microstructural Properties ◽  
Label Free ◽  
Tracer Studies ◽  
Basic Principles ◽  
The Brain ◽  
Source Of Information

Despite the impressive advances in diffusion MRI (dMRI) acquisition and analysis that have taken place during the Human Connectome era, dMRI tractography is still an imperfect source of information on the circuitry of the brain. In this review, we discuss methods for post mortem validation of dMRI tractography, fiber orientations, and other microstructural properties of axon bundles that are typically extracted from dMRI data. These methods include anatomic tracer studies, Klingler's dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.

Outcome after Asphyxial and Circulatory Disturbances in the Brain

1991 ◽  
Vol 7 (S1) ◽  
pp. 113-117 ◽  
Author(s):  
Malcolm I. Levene
Keyword(s):  
Intraventricular Hemorrhage ◽  
Imaging Techniques ◽  
Periventricular Leukomalacia ◽  
Cellular Level ◽  
Birth Process ◽  
Reasonable Degree ◽  
Definition Of ◽  
The Brain ◽  
Circulatory Disturbances

The first consideration must be an agreed-upon definition of asphyxia. We cannot determine outcome of a condition if some observers are referring to apples and others to pears. Asphyxia is a pathophysiological event comprising both hypoperfusion and hypoxia, and these events result in compromise at a cellular level with the production of metabolic acids. This can be due to a wide number of insults, but a complication of the birth process is the most important cause. Asphyxia is not like intraventricular hemorrhage (IVH) or periventricular leukomalacia (PVL), as these are conditions that can be diagnosed with a reasonable degree of precision with imaging techniques.

scholarly journals A Review of Intrinsic Optical Imaging Serial Blockface Histology (ICI-SBH) for Whole Rodent Brain Imaging

Photonics ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 66 ◽  
Author(s):  
Joël Lefebvre ◽  
Patrick Delafontaine-Martel ◽  
Frédéric Lesage
Keyword(s):  
Optical Imaging ◽  
Brain Imaging ◽  
Mouse Brain ◽  
Fluorescent Dyes ◽  
Driving Forces ◽  
Imaging Techniques ◽  
Reconstruction Algorithms ◽  
Contrast Imaging ◽  
Brain Connectome ◽  
Rodent Brain

In recent years, multiple serial histology techniques were developed to enable whole rodent brain imaging in 3-D. The main driving forces behind the emergence of these imaging techniques were the genome-wide atlas of gene expression in the mouse brain, the pursuit of the mouse brain connectome, and the BigBrain project. These projects rely on the use of optical imaging to target neuronal structures with histological stains or fluorescent dyes that are either expressed by transgenic mice or injected at specific locations in the brain. Efforts to adapt the serial histology acquisition scheme to use intrinsic contrast imaging (ICI) were also put forward, thus leveraging the natural contrast of neuronal tissue. This review focuses on these efforts. First, the origin of optical contrast in brain tissue is discussed with emphasis on the various imaging modalities exploiting these contrast mechanisms. Serial blockface histology (SBH) systems using ICI modalities are then reported, followed by a review of some of their applications. These include validation studies and the creation of multimodal brain atlases at a micrometer resolution. The paper concludes with a perspective of future developments, calling for a consolidation of the SBH research and development efforts around the world. The goal would be to offer the neuroscience community a single standardized open-source SBH solution, including optical design, acquisition automation, reconstruction algorithms, and analysis pipelines.

A Review of Various Machine Learning Techniques for Brain Tumor Detection from MRI Images

2020 ◽  
Vol 16 (8) ◽  
pp. 937-945
Author(s):  
Aaishwarya Sanjay Bajaj ◽  
Usha Chouhan
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Ct Scan ◽  
Imaging Techniques ◽  
Critical Evaluation ◽  
Tumor Detection ◽  
Machine Learning Techniques ◽  
X Rays ◽  
Detection Techniques ◽  
The Brain

Background: This paper endeavors to identify an expedient approach for the detection of the brain tumor in MRI images. The detection of tumor is based on i) review of the machine learning approach for the identification of brain tumor and ii) review of a suitable approach for brain tumor detection. Discussion: This review focuses on different imaging techniques such as X-rays, PET, CT- Scan, and MRI. This survey identifies a different approach with better accuracy for tumor detection. This further includes the image processing method. In most applications, machine learning shows better performance than manual segmentation of the brain tumors from MRI images as it is a difficult and time-consuming task. For fast and better computational results, radiology used a different approach with MRI, CT-scan, X-ray, and PET. Furthermore, summarizing the literature, this paper also provides a critical evaluation of the surveyed literature which reveals new facets of research. Conclusion: The problem faced by the researchers during brain tumor detection techniques and machine learning applications for clinical settings have also been discussed.

Brain Tumor Detection via Asymmetry Quantification across Mid Sagittal Plane

2020 ◽  
Vol 13 ◽  
Author(s):  
Shoaib Amin Banday ◽  
Mohammad Khalid Pandit
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Sagittal Plane ◽  
Early Stage ◽  
Imaging Techniques ◽  
Complex Structure ◽  
Magnetic Resonance Images ◽  
Absolute Difference ◽  
Brain Hemispheres ◽  
The Brain

Introduction: Brain tumor is among the major causes of morbidity and mortality rates worldwide. According to National Brain Tumor Foundation (NBTS), the death rate has nearly increased by as much as 300% over last couple of decades. Tumors can be categorized as benign (non-cancerous) and malignant (cancerous). The type of the brain tumor significantly depends on various factors like the site of its occurrence, its shape, the age of the subject etc. On the other hand, Computer Aided Detection (CAD) has been improving significantly in recent times. The concept, design and implementation of these systems ascend from fairly simple ones to computationally intense ones. For efficient and effective diagnosis and treatment plans in brain tumor studies, it is imperative that an abnormality is detected at an early stage as it provides a little more time for medical professionals to respond. The early detection of diseases has predominantly been possible because of medical imaging techniques developed from past many decades like CT, MRI, PET, SPECT, FMRI etc. The detection of brain tumors however, has always been a challenging task because of the complex structure of the brain, diverse tumor sizes and locations in the brain. Method: This paper proposes an algorithm that can detect the brain tumors in the presence of the Radio-Frequency (RF) inhomoginiety. The algorithm utilizes the Mid Sagittal Plane as a landmark point across which the asymmetry between the two brain hemispheres is estimated using various intensity and texture based parameters. Result: The results show the efficacy of the proposed method for the detection of the brain tumors with an acceptable detection rate. Conclusion: In this paper, we have calculated three textural features from the two hemispheres of the brain viz: Contrast (CON), Entropy (ENT) and Homogeneity (HOM) and three parameters viz: Root Mean Square Error (RMSE), Correlation Co-efficient (CC), and Integral of Absolute Difference (IAD) from the intensity distribution profiles of the two brain hemispheres to predict any presence of the pathology. First a Mid Sagittal Plane (MSP) is obtained on the Magnetic Resonance Images that virtually divides brain into two bilaterally symmetric hemispheres. The block wise texture asymmetry is estimated for these hemispheres using the above 6 parameters.

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