Multistage transfer learning for medical images
Deep learning is revolutionizing various domains and significantly impacting medical image
analysis. Despite notable progress, numerous challenges remain, necessitating the …
analysis. Despite notable progress, numerous challenges remain, necessitating the …
Brain tumor grade classification using the ConvNext architecture
Objective Brain tumor grade is an important aspect of brain tumor diagnosis and helps to
plan for treatment. Traditional methods of diagnosis, including biopsy and manual …
plan for treatment. Traditional methods of diagnosis, including biopsy and manual …
[HTML][HTML] Automated segmentation of meningioma from contrast-enhanced T1-weighted MRI images in a case series using a marker-controlled watershed …
Introduction and importance Accurate segmentation of meningiomas from contrast-
enhanced T1-weighted (CE T1-w) magnetic resonance imaging (MRI) is crucial for …
enhanced T1-weighted (CE T1-w) magnetic resonance imaging (MRI) is crucial for …
Trade-off between training and testing ratio in machine learning for medical image processing
Artificial intelligence (AI) and machine learning (ML) aim to mimic human intelligence and
enhance decision making processes across various fields. A key performance determinant …
enhance decision making processes across various fields. A key performance determinant …
An optimized dual attention-based network for brain tumor classification
B Masoudi - International Journal of System Assurance Engineering …, 2024 - Springer
Brain tumors are one of the leading causes of death worldwide. Different types of brain
tumors are known, so the choice of treatment depends directly on the type of tumor. The …
tumors are known, so the choice of treatment depends directly on the type of tumor. The …
[HTML][HTML] Deep CNNs for glioma grading on conventional MRIs: Performance analysis, challenges, and future directions
The increasing global incidence of glioma tumors has raised significant healthcare concerns
due to their high mortality rates. Traditionally, tumor diagnosis relies on visual analysis of …
due to their high mortality rates. Traditionally, tumor diagnosis relies on visual analysis of …
Melanoma Classification Through Deep Learning Using Dermoscopic Images
Melanoma is known to be the most common type of skin cancer that has a great impact on
human beings around the globe. Since melanoma cells cannot be seen with the naked eye …
human beings around the globe. Since melanoma cells cannot be seen with the naked eye …
Computer-Aided System for Pneumothorax Detection through Chest X-ray Images using Convolutional Neural Network
A pneumothorax (PTX) is a serious condition that can cause death in people because of
breathing difficulties. Therefore, the identification of lesions in the lungs, such as …
breathing difficulties. Therefore, the identification of lesions in the lungs, such as …
An Automated Hybrid Glaucoma Detection Framework through Retinal Images
Glaucoma arise ascribed to an increased enforcement inside the eye, that leads to damage
the visual nerve. Glaucoma is the world's second leading cause of blindness, after cataracts …
the visual nerve. Glaucoma is the world's second leading cause of blindness, after cataracts …
A Hybrid Deep Learning Approach for Brain Tumor Classification
MJF Sino Cruz, JDL Caro - Novel & Intelligent Digital Systems …, 2024 - Springer
A brain tumor is an abnormal cell that grows in a certain region of the brain. The
classification of tumors is usually conducted by experts in the medical field and manually …
classification of tumors is usually conducted by experts in the medical field and manually …