Biomaterial Database

Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture. 2020

Ahmet Çinar, and Muhammed Yildirim

Computer Engineering Department, Fırat University, Elazığ, Turkey. Electronic address: acinar@firat.edu.tr.

Brain tumor is one of the dangerous and deadly cancer types seen in adults and children. Early and accurate diagnosis of brain tumor is important for the treatment process. It is an important step for specialists to detect the brain tumor using computer aided systems. These systems allow specialists to perform tumor detection more easily. However, mistakes made with traditional methods are also prevented. In this paper, it is aimed to diagnose the brain tumor using MRI images. CNN models, one of the deep learning networks, are used for the diagnosis process. Resnet50 architecture, one of the CNN models, is used as the base. The last 5 layers of the Resnet50 model have been removed and added 8 new layers. With this model, 97.2% accuracy value is obtained. Also, results are obtained with Alexnet, Resnet50, Densenet201, InceptionV3 and Googlenet models. Of all these models, the model developed with the highest performance has classified the brain tumor images. As a result, when analyzed in other studies in the literature, it is concluded that the developed method is effective and can be used in computer-aided systems to detect brain tumor.

UI	MeSH Term	Description	Entries
D008279	Magnetic Resonance Imaging	Non-invasive method of demonstrating internal anatomy based on the principle that atomic nuclei in a strong magnetic field absorb pulses of radiofrequency energy and emit them as radiowaves which can be reconstructed into computerized images. The concept includes proton spin tomographic techniques.	Chemical Shift Imaging,MR Tomography,MRI Scans,MRI, Functional,Magnetic Resonance Image,Magnetic Resonance Imaging, Functional,Magnetization Transfer Contrast Imaging,NMR Imaging,NMR Tomography,Tomography, NMR,Tomography, Proton Spin,fMRI,Functional Magnetic Resonance Imaging,Imaging, Chemical Shift,Proton Spin Tomography,Spin Echo Imaging,Steady-State Free Precession MRI,Tomography, MR,Zeugmatography,Chemical Shift Imagings,Echo Imaging, Spin,Echo Imagings, Spin,Functional MRI,Functional MRIs,Image, Magnetic Resonance,Imaging, Magnetic Resonance,Imaging, NMR,Imaging, Spin Echo,Imagings, Chemical Shift,Imagings, Spin Echo,MRI Scan,MRIs, Functional,Magnetic Resonance Images,Resonance Image, Magnetic,Scan, MRI,Scans, MRI,Shift Imaging, Chemical,Shift Imagings, Chemical,Spin Echo Imagings,Steady State Free Precession MRI
D001921	Brain	The part of CENTRAL NERVOUS SYSTEM that is contained within the skull (CRANIUM). Arising from the NEURAL TUBE, the embryonic brain is comprised of three major parts including PROSENCEPHALON (the forebrain); MESENCEPHALON (the midbrain); and RHOMBENCEPHALON (the hindbrain). The developed brain consists of CEREBRUM; CEREBELLUM; and other structures in the BRAIN STEM.	Encephalon
D001932	Brain Neoplasms	Neoplasms of the intracranial components of the central nervous system, including the cerebral hemispheres, basal ganglia, hypothalamus, thalamus, brain stem, and cerebellum. Brain neoplasms are subdivided into primary (originating from brain tissue) and secondary (i.e., metastatic) forms. Primary neoplasms are subdivided into benign and malignant forms. In general, brain tumors may also be classified by age of onset, histologic type, or presenting location in the brain.	Brain Cancer,Brain Metastases,Brain Tumors,Cancer of Brain,Malignant Primary Brain Tumors,Neoplasms, Intracranial,Benign Neoplasms, Brain,Brain Neoplasm, Primary,Brain Neoplasms, Benign,Brain Neoplasms, Malignant,Brain Neoplasms, Malignant, Primary,Brain Neoplasms, Primary Malignant,Brain Tumor, Primary,Brain Tumor, Recurrent,Cancer of the Brain,Intracranial Neoplasms,Malignant Neoplasms, Brain,Malignant Primary Brain Neoplasms,Neoplasms, Brain,Neoplasms, Brain, Benign,Neoplasms, Brain, Malignant,Neoplasms, Brain, Primary,Primary Brain Neoplasms,Primary Malignant Brain Neoplasms,Primary Malignant Brain Tumors,Benign Brain Neoplasm,Benign Brain Neoplasms,Benign Neoplasm, Brain,Brain Benign Neoplasm,Brain Benign Neoplasms,Brain Cancers,Brain Malignant Neoplasm,Brain Malignant Neoplasms,Brain Metastase,Brain Neoplasm,Brain Neoplasm, Benign,Brain Neoplasm, Malignant,Brain Neoplasms, Primary,Brain Tumor,Brain Tumors, Recurrent,Cancer, Brain,Intracranial Neoplasm,Malignant Brain Neoplasm,Malignant Brain Neoplasms,Malignant Neoplasm, Brain,Neoplasm, Brain,Neoplasm, Intracranial,Primary Brain Neoplasm,Primary Brain Tumor,Primary Brain Tumors,Recurrent Brain Tumor,Recurrent Brain Tumors,Tumor, Brain
D002648	Child	A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL.	Children
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328	Adult	A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available.	Adults
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron