A review on automated cancer detection in medical images using machine learning and deep learning based computational techniques: Challenges and …
Cancer is one of the most deadly diseases diagnosed among the population across the
globe so far. The number of cases is increasing at a high pace each year that subsequently …
globe so far. The number of cases is increasing at a high pace each year that subsequently …
Vision transformers, ensemble model, and transfer learning leveraging explainable AI for brain tumor detection and classification
The abnormal growth of malignant or nonmalignant tissues in the brain causes long-term
damage to the brain. Magnetic resonance imaging (MRI) is one of the most common …
damage to the brain. Magnetic resonance imaging (MRI) is one of the most common …
A literature review on brain tumor detection and segmentation
A Miglani, H Madan, S Kumar… - 2021 5th International …, 2021 - ieeexplore.ieee.org
A tumor is a swelling or abnormal growth resulting from the division of cells in an
uncontrolled and disorderly manner. Brain tumors are an exceptionally threatening kind of …
uncontrolled and disorderly manner. Brain tumors are an exceptionally threatening kind of …
3D-MRI brain tumor detection model using modified version of level set segmentation based on dragonfly algorithm
Accurate brain tumor segmentation from 3D Magnetic Resonance Imaging (3D-MRI) is an
important method for obtaining information required for diagnosis and disease therapy …
important method for obtaining information required for diagnosis and disease therapy …
DeepTumor: framework for Brain MR image classification, Segmentation and Tumor Detection
G Latif - Diagnostics, 2022 - mdpi.com
The proper segmentation of the brain tumor from the image is important for both patients and
medical personnel due to the sensitivity of the human brain. Operation intervention would …
medical personnel due to the sensitivity of the human brain. Operation intervention would …
Ensemble classification of integrated CT scan datasets in detecting COVID-19 using feature fusion from contourlet transform and CNN
The COVID-19 disease caused by coronavirus is constantly changing due to the emergence
of different variants and thousands of people are dying every day worldwide. Early detection …
of different variants and thousands of people are dying every day worldwide. Early detection …
MRI-based brain tumor detection using the fusion of histogram oriented gradients and neural features
Computer-aided diagnoses are playing a remarkable role in analyzing the MRI images and
thus assist the radiologist. The brain tumor is one of the most common and incursive …
thus assist the radiologist. The brain tumor is one of the most common and incursive …
[HTML][HTML] Using fused Contourlet transform and neural features to spot COVID19 infections in CT scan images
Abstract The World Health Organization (WHO) claims that COVID19 is the pandemic
disease of the 22 nd century. The COVID19 disease is caused by a strain of coronavirus that …
disease of the 22 nd century. The COVID19 disease is caused by a strain of coronavirus that …
[PDF][PDF] Deep learning-based car seatbelt classifier resilient to weather conditions
O Hosam - Int. J. Eng. Technol, 2020 - researchgate.net
Deep Learning is a very promising field in image classification. It leads to the automation of
many real-world problems. Currently, Car seatbelt violation detection is done manually or …
many real-world problems. Currently, Car seatbelt violation detection is done manually or …
Useful or not? A review filtering system based on hybrid methods
J Kim, Y Jang, W Seo, H Lee - Aslib Journal of Information …, 2024 - emerald.com
Purpose Information filtering systems serve as robust tools in the ongoing difficulties
associated with overwhelming volumes of data. With constant generation and accumulation …
associated with overwhelming volumes of data. With constant generation and accumulation …