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Field: Neurology

Brain Tumor Classification Using Convolutional Neural Network

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Sunanda Das, O. F. M. Riaz Rahman Aranya, Nishat Nayla Labiba

Journal: 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT) 2019
Year:
Citations: 215

Medical image classification has gained tremendous attention in recent years, and Convolutional Neural Network (CNN) is the most widespread neural network model for image classification problem. CNN is designed to determine features adaptively through backpropagation by applying numerous building bl...

Life SciencesNeuroscienceNeurology
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Vision Transformers, Ensemble Model, and Transfer Learning Leveraging Explainable AI for Brain Tumor Detection and Classification

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Shahriar Hossain, Amitabha Chakrabarty, Thippa Reddy Gadekallu, Mamoun Alazab et al.

Journal: IEEE Journal of Biomedical and Health InformaticsYear: 2023Citations: 206

The abnormal growth of malignant or nonmalignant tissues in the brain causes long-term damage to the brain. Magnetic resonance imaging (MRI) is one of the most common methods of detecting brain tumors. To determine whether a patient has a brain tumor, MRI filters are physically examined by experts a...

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Axonal variant of Guillain-Barre syndrome associated with <i>Campylobacter</i> infection in Bangladesh

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Zhahirul Islam, Bart C. Jacobs, Alex van Belkum, Quazi Deen Mohammad et al.

Journal: NeurologyYear: 2010Citations: 199

BACKGROUND: Campylobacter jejuni enteritis is the predominant bacterial infection preceding Guillain-Barré syndrome (GBS), an acute postinfectious immune-mediated polyradiculoneuropathy. The purpose of this study was to define the clinical phenotype of GBS and the relation with preceding C jejuni in...

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MRI brain tumor detection and classification using parallel deep convolutional neural networks

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Takowa Rahman, Md. Saiful Islam

Journal: Measurement SensorsYear: 2023Citations: 197

Convolutional neural network (CNN) is widely used to classify brain tumors with high accuracy. Since CNN collects features randomly without knowing the local and global features and causes overfitting problems, this research proposes a novel parallel deep convolutional neural network (PDCNN) topolog...

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An efficient deep learning model to categorize brain tumor using reconstruction and fine-tuning

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Md. Alamin Talukder, Md. Manowarul Islam, Md. Ashraf Uddin, Arnisha Akhter et al.

Journal: Expert Systems with ApplicationsYear: 2023Citations: 193

Brain tumors are among the most fatal and devastating diseases, often resulting in significantly reduced life expectancy. An accurate diagnosis of brain tumors is crucial to devise treatment plans that can extend the lives of affected individuals. Manually identifying and analyzing large volumes of ...

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A classification of MRI brain tumor based on two stage feature level ensemble of deep CNN models

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Nahid Ferdous Aurna, Mohammad Abu Yousuf, Kazi Abu Taher, AKM Azad et al.

Journal: Computers in Biology and MedicineYear: 2022Citations: 192

The brain tumor is one of the deadliest cancerous diseases and its severity has turned it to the leading cause of cancer related mortality. The treatment procedure of the brain tumor depends on the type, location and size of the tumor. Relying solely on human inspection for precise categorization ca...

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Deep Learning Based Brain Tumor Detection and Classification

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Nadim Mahmud Dipu, Sifatul Alam Shohan, K. M. A. Salam

Journal: 2021 International Conference on Intelligent Technologies (CONIT)Year: 2021Citations: 185

One of the most crucial tasks of neurologists and radiologists is early brain tumor detection. However, manually detecting and segmenting brain tumors from Magnetic Resonance Imaging (MRI) scans is challenging, and prone to errors. That is why an automated brain tumor detection system is required fo...

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AlzheimerNet: An Effective Deep Learning Based Proposition for Alzheimer’s Disease Stages Classification From Functional Brain Changes in Magnetic Resonance Images

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F. M. Javed Mehedi Shamrat, Shamima Akter, Sami Azam, Asif Karim et al.

Journal: IEEE AccessYear: 2023Citations: 184

Alzheimer’s disease is largely the underlying cause of dementia due to its progressive neurodegenerative nature among the elderly. The disease can be divided into five stages: Subjective Memory Concern (SMC), Mild Cognitive Impairment (MCI), Early MCI (EMCI), Late MCI (LMCI), and Alzheimer’s Disease...

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The Vertebral Venous Plexus as a Major Cerebral Venous Outflow Tract

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Henry Epstein, H. W. Linde, A. R. Crompton, I. S. Cine et al.

Journal: AnesthesiologyYear: 1970Citations: 183

Cerebral venous outflow in rhesus monkeys anesthetized with halothane has been studied by angiographic techniques. The effects of body position and pressure within the airway have been studied. With the monkey supine, injection of radiopaque contrast medium into the superior sagittal sinus permitted

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Brain tumor detection in MR image using superpixels, principal component analysis and template based K-means clustering algorithm

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Md Khairul Islam, Md Shahin Ali, Md Sipon Miah, Mahbubur Rahman et al.

Journal: Machine Learning with ApplicationsYear: 2021Citations: 182

In the present era, human brain tumor is the extremist dangerous and devil to the human being that leads to certain death. Furthermore, the brain tumor arises more complexity of patients life with time. As a result, early detection of tumors is most crucial to save and prolong the patient’s lifetime...

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Developing and validating Parkinson’s disease subtypes and their motor and cognitive progression

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Michael Lawton, Yoav Ben‐Shlomo, Margaret May, Fahd Baig et al.

Journal: Journal of Neurology Neurosurgery & PsychiatryYear: 2018Citations: 182

Objectives To use a data-driven approach to determine the existence and natural history of subtypes of Parkinson’s disease (PD) using two large independent cohorts of patients newly diagnosed with this condition. Methods 1601 and 944 patients with idiopathic PD, from Tracking Parkinson’s and Discove...

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Automatic Human Brain Tumor Detection in MRI Image Using Template-Based K Means and Improved Fuzzy C Means Clustering Algorithm

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Md Shahariar Alam, Md Mahbubur Rahman, Mohammad Amzad Hossain, Md Khairul Islam et al.

Journal: Big Data and Cognitive ComputingYear: 2019Citations: 178

In recent decades, human brain tumor detection has become one of the most challenging issues in medical science. In this paper, we propose a model that includes the template-based K means and improved fuzzy C means (TKFCM) algorithm for detecting human brain tumors in a magnetic resonance imaging (M...

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Tight junctions in Schwann cells of peripheral myelinated axons

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Tatsuo Miyamoto, Kazumasa Morita, Daisuke Takemoto, Kosei Takeuchi et al.

Journal: The Journal of Cell BiologyYear: 2005Citations: 165

Tight junction (TJ)-like structures have been reported in Schwann cells, but their molecular composition and physiological function remain elusive. We found that claudin-19, a novel member of the claudin family (TJ adhesion molecules in epithelia), constituted these structures. Claudin-19-deficient ...

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TimeDistributed-CNN-LSTM: A Hybrid Approach Combining CNN and LSTM to Classify Brain Tumor on 3D MRI Scans Performing Ablation Study

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Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Md. Zahid Hasan et al.

Journal: IEEE AccessYear: 2022Citations: 163

Identification of brain tumors and accurate grading at an early stage are crucial in cancer diagnosis, as a timely diagnosis can increase the chances of survival. Considering the challenges and risks of tumor biopsies, noninvasive imaging procedures such as Magnetic Resonance Imaging (MRI) are exten...

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Copper induces microglia-mediated neuroinflammation through ROS/NF-κB pathway and mitophagy disorder

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Qian Zhou, Ying Zhang, Lu Lu, Hu Zhang et al.

Journal: Food and Chemical ToxicologyYear: 2022Citations: 153

The epidemiological correlation between copper exposure and higher risk of Parkinson disease (PD) has been recognized for a long time, and microglia-mediated neuroinflammation has reported to be an important component of the pathogenesis of PD. The present study aimed to investigate the role of micr...

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