Image segmentation for MR brain tumor detection using machine learning: a review
Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain
disease and monitor treatment as non-invasive imaging technology. MRI produces three …
disease and monitor treatment as non-invasive imaging technology. MRI produces three …
Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives
A brain tumor is an abnormal mass of tissue located inside the skull. In addition to putting
pressure on the healthy parts of the brain, it can lead to significant health problems …
pressure on the healthy parts of the brain, it can lead to significant health problems …
MRI-based brain tumor classification using ensemble of deep features and machine learning classifiers
Brain tumor classification plays an important role in clinical diagnosis and effective
treatment. In this work, we propose a method for brain tumor classification using an …
treatment. In this work, we propose a method for brain tumor classification using an …
Brain tumor classification using a hybrid deep autoencoder with Bayesian fuzzy clustering-based segmentation approach
PMS Raja - Biocybernetics and Biomedical Engineering, 2020 - Elsevier
In medical image processing, brain tumor detection and segmentation is a challenging and
time-consuming task. Magnetic Resonance Image (MRI) scan analysis is a powerful tool in …
time-consuming task. Magnetic Resonance Image (MRI) scan analysis is a powerful tool in …
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 …
[HTML][HTML] Brain tumor segmentation of MR images using SVM and fuzzy classifier in machine learning
R Vankdothu, MA Hameed - Measurement: Sensors, 2022 - Elsevier
Medical image processing is a rapidly growing and concentrating topic today. Medical
image analysis techniques are used to diagnose and cure illnesses. One such fundamental …
image analysis techniques are used to diagnose and cure illnesses. One such fundamental …
Cascading handcrafted features and Convolutional Neural Network for IoT-enabled brain tumor segmentation
Abstract The Internet of Things (IoT) has revolutionized the medical world by facilitating data
acquisition using various IoT devices. These devices generate the data in multiple forms …
acquisition using various IoT devices. These devices generate the data in multiple forms …
Brain image identification and classification on Internet of Medical Things in healthcare system using support value based deep neural network
R Vankdothu, MA Hameed, A Ameen… - Computers and Electrical …, 2022 - Elsevier
Abstract The Internet of Medical Things (IoMT) combines the Internet of Things (IoT) with
medical equipment to provide better patient comfort, cost-effective medical solutions, faster …
medical equipment to provide better patient comfort, cost-effective medical solutions, faster …
[HTML][HTML] Analysis of brain MRI images using improved cornernet approach
The brain tumor is a deadly disease that is caused by the abnormal growth of brain cells,
which affects the human blood cells and nerves. Timely and precise detection of brain …
which affects the human blood cells and nerves. Timely and precise detection of brain …
Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment
This review delves into the most recent advancements in applying artificial intelligence (AI)
within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors …
within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors …