A hybrid deep learning-based approach for brain tumor classification
Brain tumors (BTs) are spreading very rapidly across the world. Every year, thousands of
people die due to deadly brain tumors. Therefore, accurate detection and classification are …
people die due to deadly brain tumors. Therefore, accurate detection and classification are …
[HTML][HTML] Efficient and low complex architecture for detection and classification of Brain Tumor using RCNN with Two Channel CNN
N Kesav, MG Jibukumar - Journal of King Saud University-Computer and …, 2022 - Elsevier
Abstract The Brain Tumor is one of the most serious scenarios associated with the brain
where a cluster of abnormal cells grows in an uncontrolled fashion. The field of image …
where a cluster of abnormal cells grows in an uncontrolled fashion. The field of image …
A review of diagnostic strategies for pulmonary embolism prediction in computed tomography pulmonary angiograms
Pulmonary Embolism (PE) occurs when blood clots travel to the lungs from different parts of
the body. It is amongst the most lethal cardio-respiratory diseases after stroke and heart …
the body. It is amongst the most lethal cardio-respiratory diseases after stroke and heart …
A sequential machine learning-cum-attention mechanism for effective segmentation of brain tumor
Magnetic resonance imaging is the most generally utilized imaging methodology that
permits radiologists to look inside the cerebrum using radio waves and magnets for tumor …
permits radiologists to look inside the cerebrum using radio waves and magnets for tumor …
[HTML][HTML] An optimized XGBoost technique for accurate brain tumor detection using feature selection and image segmentation
CJ Tseng, C Tang - Healthcare Analytics, 2023 - Elsevier
An abnormal multiplication of cells in the brain forms malignant and benign brain tumors.
Malignant brain tumors are more prevalent than benign ones. Detecting a tumor's physical …
Malignant brain tumors are more prevalent than benign ones. Detecting a tumor's physical …
Quantum algorithm for quicker clinical prognostic analysis: an application and experimental study using CT scan images of COVID-19 patients
K Sengupta, PR Srivastava - BMC Medical Informatics and Decision …, 2021 - Springer
Background In medical diagnosis and clinical practice, diagnosing a disease early is crucial
for accurate treatment, lessening the stress on the healthcare system. In medical imaging …
for accurate treatment, lessening the stress on the healthcare system. In medical imaging …
RCS-YOLO: A fast and high-accuracy object detector for brain tumor detection
With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks
have become one of the most efficient algorithms for object detection. However, the …
have become one of the most efficient algorithms for object detection. However, the …
[PDF][PDF] Segmenting and classifiying the brain tumor from MRI medical images based on machine learning algorithms: A review
ABSTRACT A brain tumor is a problem that threatens life and impedes the normal working of
the human body. The brain tumor needs to be identified early for the proper diagnosis and …
the human body. The brain tumor needs to be identified early for the proper diagnosis and …
An improved hybrid classification of brain tumor MRI images based on conglomeration feature extraction techniques
The brain seems to be the most complex organ in the human body and operates as the
central part of the nervous system. The classification of brain tumors is the most complicated …
central part of the nervous system. The classification of brain tumors is the most complicated …
An explainable brain tumor detection and classification model using deep learning and layer-wise relevance propagation
The Brain tumor is the most common and devastating problem nowadays. Many people die
every day as a result of a tumor's late detection, and these lives could have been saved if the …
every day as a result of a tumor's late detection, and these lives could have been saved if the …