An enhanced deep learning approach for brain cancer MRI images classification using residual networks
Cancer is the second leading cause of death after cardiovascular diseases. Out of all types
of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types …
of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types …
[HTML][HTML] Dynamic architecture based deep learning approach for glioblastoma brain tumor survival prediction
DS Wankhede, R Selvarani - Neuroscience Informatics, 2022 - Elsevier
A correct diagnosis of brain tumours is crucial to making an accurate treatment plan for
patients with the disease and allowing them to live a long and healthy life. Among a few …
patients with the disease and allowing them to live a long and healthy life. Among a few …
An enhanced deep learning method for multi-class brain tumor classification using deep transfer learning
Multi-class brain tumor classification is an important area of research in the field of medical
imaging because of the different tumor characteristics. One such challenging problem is the …
imaging because of the different tumor characteristics. One such challenging problem is the …
MRI brain tumor image classification using a combined feature and image-based classifier
A Veeramuthu, S Meenakshi, G Mathivanan… - Frontiers in …, 2022 - frontiersin.org
Brain tumor classification plays a niche role in medical prognosis and effective treatment
process. We have proposed a combined feature and image-based classifier (CFIC) for brain …
process. We have proposed a combined feature and image-based classifier (CFIC) for brain …
A novel extended Kalman filter with support vector machine based method for the automatic diagnosis and segmentation of brain tumors
B Chen, L Zhang, H Chen, K Liang, X Chen - Computer Methods and …, 2021 - Elsevier
Background Brain tumors are life-threatening, and their early detection is crucial for
improving survival rates. Conventionally, brain tumors are detected by radiologists based on …
improving survival rates. Conventionally, brain tumors are detected by radiologists based on …
Detecting brain tumors using deep learning convolutional neural network with transfer learning approach
Accurate classification of brain tumor subtypes is important for prognosis and treatment. In
this study, we optimized and applied non‐deep learning methods based on hand‐crafted …
this study, we optimized and applied non‐deep learning methods based on hand‐crafted …
Bayesian dynamic profiling and optimization of important ranked energy from gray level co-occurrence (GLCM) features for empirical analysis of brain MRI
Accurate classification of brain tumor subtypes is important for prognosis and treatment.
Researchers are develo** tools based on static and dynamic feature extraction and …
Researchers are develo** tools based on static and dynamic feature extraction and …
[PDF][PDF] Neuroendoscopy Adapter Module Development for Better Brain Tumor Image Visualization.
The issue of brain magnetic resonance image exploration together with classification
receives a significant awareness in recent years. Indeed, various computer-aided-diagnosis …
receives a significant awareness in recent years. Indeed, various computer-aided-diagnosis …
[PDF][PDF] Pneumonia detection and classification using CNN and VGG16
Pneumonia, an infectious disease caused by a bacterium in the lungs' alveoli, is frequently
the result of pollution. A lung infection causes pus to build up in the affected tissue …
the result of pollution. A lung infection causes pus to build up in the affected tissue …
Review on Cardiac Arrhythmia Through Segmentation Approaches in Deep Learning
Abstract Identifying the precise Heart Sounds (HS) positions inside a Phonocardiogram
(PCG); otherwise, Heart Sounds Segmentation (HSS) is a vital phase for the automatic …
(PCG); otherwise, Heart Sounds Segmentation (HSS) is a vital phase for the automatic …