Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
Review on the evaluation and development of artificial intelligence for COVID-19 containment
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a
substantiated promise of continuous applicability in the real world domain. Artificial …
substantiated promise of continuous applicability in the real world domain. Artificial …
[HTML][HTML] Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images
R Ranjbarzadeh, A Bagherian Kasgari… - Scientific Reports, 2021 - nature.com
Brain tumor localization and segmentation from magnetic resonance imaging (MRI) are hard
and important tasks for several applications in the field of medical analysis. As each brain …
and important tasks for several applications in the field of medical analysis. As each brain …
Intelligent model for brain tumor identification using deep learning
Brain tumors can be a major cause of psychiatric complications such as depression and
panic attacks. Quick and timely recognition of a brain tumor is more effective in tumor …
panic attacks. Quick and timely recognition of a brain tumor is more effective in tumor …
HECON: Weight assessment of the product loyalty criteria considering the customer decision's halo effect using the convolutional neural networks
The economic pressures and increasing competition in markets have led to the CEOs of
companies being forced to make the right strategic decisions in the development of products …
companies being forced to make the right strategic decisions in the development of products …
ME-CCNN: Multi-encoded images and a cascade convolutional neural network for breast tumor segmentation and recognition
R Ranjbarzadeh, S Jafarzadeh Ghoushchi… - Artificial Intelligence …, 2023 - Springer
Breast tumor segmentation and recognition from mammograms play a key role in healthcare
and treatment services. As different tumors in mammography have dissimilar densities …
and treatment services. As different tumors in mammography have dissimilar densities …
MRFE-CNN: Multi-route feature extraction model for breast tumor segmentation in Mammograms using a convolutional neural network
R Ranjbarzadeh, N Tataei Sarshar… - Annals of Operations …, 2023 - Springer
Breast cancer is cancer that develops from the breast tissue and has been recognized as
one of the most dangerous and deadly diseases that is the second leading cause of cancer …
one of the most dangerous and deadly diseases that is the second leading cause of cancer …
Nerve optic segmentation in CT images using a deep learning model and a texture descriptor
R Ranjbarzadeh, S Dorosti… - Complex & Intelligent …, 2022 - Springer
The increased intracranial pressure (ICP) can be described as an increase in pressure
around the brain and can lead to serious health problems. The assessment of ultrasound …
around the brain and can lead to serious health problems. The assessment of ultrasound …
TPCNN: two-path convolutional neural network for tumor and liver segmentation in CT images using a novel encoding approach
Automatic liver and tumour segmentation in CT images are crucial in numerous clinical
applications, such as postoperative assessment, surgical planning, and pathological …
applications, such as postoperative assessment, surgical planning, and pathological …
Hemorrhage semantic segmentation in fundus images for the diagnosis of diabetic retinopathy by using a convolutional neural network
Because retinal hemorrhage is one of the earliest symptoms of diabetic retinopathy, its
accurate identification is essential for early diagnosis. One of the major obstacles …
accurate identification is essential for early diagnosis. One of the major obstacles …