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Computer-aided Diagnosis (CAD) System for Determining Histological Grading of Astrocytoma Based on Ki67 Counting
Published in Varun Bajaj, G.R. Sinha, Computer-aided Design and Diagnosis Methods for Biomedical Applications, 2021
Fahmi Akmal Dzulkifli, Maryam Ahmad Sharifuddin, Mohd Yusoff Mashor, Hasnan Jaafar
Generally, brain tumors can be divided into two categories. These categories are known as primary brain tumors and metastatic brain tumors [7]. The primary brain tumor is defined as a tumor originally derived from the neoplastic cells of the brain. A metastatic or also known as a secondary brain tumor is a tumor that begins to develop elsewhere in the body and then spreads to the brain to form a new tumor. A primary brain tumor can be divided into two types: glioma and non-glioma. A glioma tumor is a tumor that grows from a glial cell. Glial cells act as supportive tissues in the brain, and they are responsible for providing support and protection for the neurons. Astrocytes, oligodendrocytes, ependymal cells, Schwann cells, satellite cells, and microglia are examples of supporting tissues in the brain [1]. Examples of glioma tumors include astrocytoma, oligodendroglioma, ependymoma, and brain stem glioma. Non-glioma tumors are tumors that form and arise from cells within the brain that are not glial cells. Examples of types of non-glioma tumors are meningioma, medulloblastoma, craniopharyngioma, and pineal gland and pituitary gland tumors.
Digital Image Processing and Three-Dimensional Reconstruction in the Basic Neurosciences
Published in Rangachar Kasturi, Mohan M. Trivedi, Image Analysis Applications, 2020
Modern neuroscience had its beginning in the late 19th century, with the discovery by Golgi of a silver stain that is selectively absorbed by a small number of neurons in thin sections of the brain (Fig. 5.1). Under light microscopy, the Golgi stain rendered visible single neurons throughout the full extent of their dendritic processes. Cajal, using Golgi’s stain, showed that the brain consists of two main classes of cells (neurons and glial cells), that the neurons are discrete cells, and that they are the basic signaling units of the brain (Nauta and Feirtag/1986). Neurons communicate with other neurons by releasing chemicals (neurotransmitters) that travel across gaps (synapses) that physically separate neurons and bind to specialized protein complexes (receptors) on the destination (postsynaptic) neuron. Within a neuron, the transfer of a signal from place to place occurs by means of the electrochemical action potential. Each neuron feels the contacts of hundreds or thousands of other neurons and projects dozens or hundreds of dendrites onto other neurons. How a neuron, feeling the inputs from many other cells, decides to transmit or not transmit a signal is a question of urgent interest and the subject of intense study currently (Kandel and Schwartz/1985).
Electrochemical Properties of Nanoporous Based Materials
Published in Mahmood Aliofkhazraei, Advances in Nanostructured Composites, 2019
Tebogo P. Tsele, Abolanle S. Adekunle, Omolola E. Fayemi, Lukman O. Olasunkanmi, Eno E. Ebenso
Dopamine is one of the most important neurotransmitters and is present in mammalian central nervous system (Sawa and Snyder 2002). Neurotransmitters are chemical messengers that transmit a message from one neuron to the next (Michael and Wightman 1999). Dopamine is a catecholamine in the form of the large organic cations and belongs to the family of excitatory chemical cardiovascular, renal and hormonal system (Velasco and Luchsinger 1998, Mo and Ogorevc 2001). In humans, a deficiency of the neurotransmitter dopamine in the basal ganglia of the brain has been known well to play a critical role in Parkinson’s disease (Agid et al. 1987). Parkinson’s disease is a degenerative disease of the nervous system associated with trembling of the arms and legs, stiffness and rigidity of the muscle and slowness of movement.
Artificial intelligence techniques for the vibration, noise, and emission characteristics of a hydrogen-enriched diesel engine
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2019
Sefa Yıldırım, Erdi Tosun, Ahmet Çalık, İhsan Uluocak, Ercan Avşar
The main idea behind the majority of the AI techniques is to simulate the functions of living cells (Tosun et al. 2017). Biologically, human neurons consist of a bunch of dendrites emanating from the cell body, a cell nucleus (processor), and an axon (output). The chemically triggered signals collected by dendrites; then they were summed up and processed by DNA located on the nucleus. Therefore, axons deliver the processed signal using synapses which are joint to the next neuron cell. ANN can be considered in this concept as a computational configuration of the behavior of these alive brain cells. ANN is particularly based on the imitation of neurons which dynamically process the information in reply to inputs (Najafi et al. 2009). The working principle of neural network predicates on processing the strength of data between two interconnected neurons. The strength of data is called as weight, and it contains the knowledge gained during training, testing, and validation. Learning is obtained by adapting the weights with reference to the input patterns. The alterations in the weights provide the adaptability to new situations (Javed et al. 2016, 2015). Consequently, ANN can predict the future from the data obtained in the past and be considered as an effective tool for simulation of engineering applications (Thakur, Mer, and Kaviti 2017).
Design of a new CMOS Low-Power Analogue Neuron
Published in IETE Journal of Research, 2018
Andisheh Ghomi, Mehdi Dolatshahi
The structure of the biological neural networks include large set of parallel processors called neurons that act together to solve a problem. A neuron receives signals from other neurons through connections called synapses. The combination of these signals, in excess of a certain threshold or activation level, results in the neuron firing. Artificial neural networks are models of biological neural structures. The starting point for most artificial neural networks is a neuron model. As it is shown in Figure 1, the neuron consists of multiple inputs and a single output. Each input is multiplied by a weight. The neuron combines these weighted inputs to pass through the activation function. The artificial neuron given in Figure 1, has n inputs, denoted as x1, x2,…, xn. Weights are denoted as w1, w2, …, wn, respectively. Weights in the artificial model are corresponded to the synaptic connections in biological neurons. Processing elements are typically modelled by two equations which represent the model of an artificial neuron as follows:where a is the weighted summation of the inputs, and f (a) is the activation function of the weighted sum.
Mechanism of peripheral nerve modulation and recent applications
Published in International Journal of Optomechatronics, 2021
Heejae Shin, Minseok Kang, Sanghoon Lee
The main structure of the PNS is a nerve that has an enclosed structure like a cable bundle in which neurons are gathered, playing the role of the passage for the electrochemical signals. As shown in Figure 1(a), a neuron consists of a cell body with the nucleus, a dendrite that receives nerve signals, generating an action potential when the signals exceed the threshold, and an axon that transmits the generated signals to an axon terminal to transfer the signal to another neuron. In some cases, this axon is covered with a myelin sheath, making the speed transmission is significantly faster compared to the unmyelinated neurons, which are covered with connective tissue called the endoneurium. In addition, the axon terminal forms a synapse with adjacent neurons, in which the electrical signal transmitted through the axon is converted into a chemical signal by releasing a molecule called a neurotransmitter that is a chemical messenger inhibiting or activating the neuron by influencing the receptor on the targeted neuron or organ. The aggregate of these nerve fibers is called a fascicle, and this fascicle is surrounded by connective tissue called the perineurium. Inside the fascicle, afferent fibers that send afferent (sensory) signals to the CNS and efferent fibers that send efferent (motor) signals from the CNS could be both located in a fascicle or a nerve which is called a mixed nerve fiber. The group of fascicles is called a nerve. A nerve is surrounded by epineurium, and it also consists of blood vessels that provide nutrients for the whole structure. (Figure 1(b)).[10]