A systematic review on metaheuristic optimization techniques for feature selections in disease diagnosis: open issues and challenges
There is a need for some techniques to solve various problems in today's computing world.
Metaheuristic algorithms are one of the techniques which are capable of providing practical …
Metaheuristic algorithms are one of the techniques which are capable of providing practical …
Moth flame optimization: theory, modifications, hybridizations, and applications
The Moth flame optimization (MFO) algorithm belongs to the swarm intelligence family and is
applied to solve complex real-world optimization problems in numerous domains. MFO and …
applied to solve complex real-world optimization problems in numerous domains. MFO and …
SwinBTS: A method for 3D multimodal brain tumor segmentation using swin transformer
Brain tumor semantic segmentation is a critical medical image processing work, which aids
clinicians in diagnosing patients and determining the extent of lesions. Convolutional neural …
clinicians in diagnosing patients and determining the extent of lesions. Convolutional neural …
VGG19 network assisted joint segmentation and classification of lung nodules in CT images
Pulmonary nodule is one of the lung diseases and its early diagnosis and treatment are
essential to cure the patient. This paper introduces a deep learning framework to support the …
essential to cure the patient. This paper introduces a deep learning framework to support the …
An improved moth flame optimization algorithm based on modified dynamic opposite learning strategy
Moth flame optimization (MFO) algorithm is a relatively new nature-inspired optimization
algorithm based on the moth's movement towards the moon. Premature convergence and …
algorithm based on the moth's movement towards the moon. Premature convergence and …
A new deep hybrid boosted and ensemble learning-based brain tumor analysis using MRI
Brain tumor analysis is essential to the timely diagnosis and effective treatment of patients.
Tumor analysis is challenging because of tumor morphology factors like size, location …
Tumor analysis is challenging because of tumor morphology factors like size, location …
A hybrid moth flame optimization algorithm for global optimization
Abstract The Moth Flame Optimization (MFO) algorithm shows decent performance results
compared to other meta-heuristic algorithms for tackling non-linear constrained global …
compared to other meta-heuristic algorithms for tackling non-linear constrained global …
Self-adaptive moth flame optimizer combined with crossover operator and Fibonacci search strategy for COVID-19 CT image segmentation
The COVID-19 is one of the most significant obstacles that humanity is now facing. The use
of computed tomography (CT) images is one method that can be utilized to recognize …
of computed tomography (CT) images is one method that can be utilized to recognize …
Breast DCE-MRI segmentation for lesion detection using chimp optimization algorithm
The high prevalence of breast cancer in women has increased dramatically in recent times.
Physician's knowledge in breast cancer diagnosis and detection using computerized …
Physician's knowledge in breast cancer diagnosis and detection using computerized …
Segmentation of brain MRI using an altruistic Harris Hawks' Optimization algorithm
Segmentation is an essential requirement in medicine when digital images are used in
illness diagnosis, especially, in posterior tasks as analysis and disease identification. An …
illness diagnosis, especially, in posterior tasks as analysis and disease identification. An …