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Deep learning models and traditional automated techniques for brain tumor segmentation in MRI: a review
Brain is an amazing organ that controls all activities of a human. Any abnormality in the
shape of anatomical regions of the brain needs to be detected as early as possible to reduce …
shape of anatomical regions of the brain needs to be detected as early as possible to reduce …
Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …
problems for people with a detrimental effect on the functioning of the nervous system. In …
A machine learning-based framework for diagnosis of COVID-19 from chest X-ray images
Abstract Corona virus disease (COVID-19) acknowledged as a pandemic by the WHO and
mankind all over the world is vulnerable to this virus. Alternative tools are needed that can …
mankind all over the world is vulnerable to this virus. Alternative tools are needed that can …
Generative adversarial networks and its applications in the biomedical image segmentation: a comprehensive survey
Recent advancements with deep generative models have proven significant potential in the
task of image synthesis, detection, segmentation, and classification. Segmenting the medical …
task of image synthesis, detection, segmentation, and classification. Segmenting the medical …
BiO-Net: learning recurrent bi-directional connections for encoder-decoder architecture
U-Net has become one of the state-of-the-art deep learning-based approaches for modern
computer vision tasks such as semantic segmentation, super resolution, image denoising …
computer vision tasks such as semantic segmentation, super resolution, image denoising …
Review of deep learning approaches for the segmentation of multiple sclerosis lesions on brain MRI
In recent years, there have been multiple works of literature reviewing methods for
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
Multiple sclerosis lesion analysis in brain magnetic resonance images: techniques and clinical applications
Multiple sclerosis (MS) is a chronic inflammatory and degenerative disease of the central
nervous system, characterized by the appearance of focal lesions in the white and gray …
nervous system, characterized by the appearance of focal lesions in the white and gray …
A survey of deep learning models in medical therapeutic areas
Artificial intelligence is a broad field that comprises a wide range of techniques, where deep
learning is presently the one with the most impact. Moreover, the medical field is an area …
learning is presently the one with the most impact. Moreover, the medical field is an area …
[HTML][HTML] BTS-GAN: computer-aided segmentation system for breast tumor using MRI and conditional adversarial networks
Breast tumor is one of the most prominent indicators for the diagnosis of breast cancer. The
precise segmentation of tumors is crucial for enhancing the accuracy of breast cancer …
precise segmentation of tumors is crucial for enhancing the accuracy of breast cancer …
US2Mask: Image-to-mask generation learning via a conditional GAN for cardiac ultrasound image segmentation
Cardiac ultrasound (US) image segmentation is vital for evaluating clinical indices, but it
often demands a large dataset and expert annotations, resulting in high costs for deep …
often demands a large dataset and expert annotations, resulting in high costs for deep …