Probabilistic neural networks: a brief overview of theory, implementation, and application
Probabilistic neural networks (PNNs) offer a scalable alternative to the conventional back-
propagation neural networks in classification problems without the need for massive forward …
propagation neural networks in classification problems without the need for massive forward …
Brain tumor detection using convolutional neural network
Brain Tumor segmentation is one of the most crucial and arduous tasks in the terrain of
medical image processing as a human-assisted manual classification can result in …
medical image processing as a human-assisted manual classification can result in …
Context aware deep learning for brain tumor segmentation, subtype classification, and survival prediction using radiology images
A brain tumor is an uncontrolled growth of cancerous cells in the brain. Accurate
segmentation and classification of tumors are critical for subsequent prognosis and …
segmentation and classification of tumors are critical for subsequent prognosis and …
[PDF][PDF] Artificial intelligence techniques for cancer detection and classification: review study
Cancer is the general name for a group of more than 100 diseases. Although cancer
includes different types of diseases, they all start because abnormal cells grow out of control …
includes different types of diseases, they all start because abnormal cells grow out of control …
Enhanced brain tumor classification using graph convolutional neural network architecture
Abstract The Brain Tumor presents a highly critical situation concerning the brain,
characterized by the uncontrolled growth of an abnormal cell cluster. Early brain tumor …
characterized by the uncontrolled growth of an abnormal cell cluster. Early brain tumor …
[PDF][PDF] Automated brain tumor detection and identification using image processing and probabilistic neural network techniques
In this paper, modified image segmentation techniques were applied on MRI scan images in
order to detect brain tumors. Also in this paper, a modified Probabilistic Neural Network …
order to detect brain tumors. Also in this paper, a modified Probabilistic Neural Network …
Information retrieves from brain MRI images for tumor detection using hybrid technique K-means and artificial neural network (KMANN)
Medical imaging plays a significant role in the field of medical science. In present scenario
image segmentation is used to extract abnormal tissues from normal tissues clearly in …
image segmentation is used to extract abnormal tissues from normal tissues clearly in …
[PDF][PDF] Extraction of texture features using GLCM and shape features using connected regions
SK PS, D Vs - International journal of engineering and technology, 2016 - researchgate.net
Feature extraction is an important step in Computer Assisted Diagnosis of brain
abnormalities using Magnetic Resonance Images (MRI). Feature Extraction is the process of …
abnormalities using Magnetic Resonance Images (MRI). Feature Extraction is the process of …
Combination of political optimizer, particle swarm optimizer, and convolutional neural network for brain tumor detection
AH Bashkandi, K Sadoughi, F Aflaki… - … Signal Processing and …, 2023 - Elsevier
Manual detection of brain and tumor tissues takes a long time and is dependent on the state
of the operator due to the great complexity of brain tissues. Experts are also required to …
of the operator due to the great complexity of brain tissues. Experts are also required to …
Brain tumor classification using discrete cosine transform and probabilistic neural network
D Sridhar, IVM Krishna - 2013 International Conference on …, 2013 - ieeexplore.ieee.org
In this paper, a new method for Brain Tumor Classification using Probabilistic Neural
Network with Discrete Cosine Transformation is proposed. The conventional method for …
Network with Discrete Cosine Transformation is proposed. The conventional method for …