A Novel Approach Based on Marine Predators Algorithm for Medical Image Enhancement

Dinh, Phu‐Hung

doi:10.1007/s11220-023-00411-y

Cited by 14 publications

(1 citation statement)

References 63 publications

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“…For instance, Duan et al (2021) used SML in combination with a Genetic Algorithm (GA) and a log-Gabor filter. A method based on fuzzy logic and Particle Swarm Optimization (PSO) has been presented by Gao et al (2021) The marine predator's algorithm (Dinh, 2023), equilibrium optimization algorithm (Dinh, 2021b), grasshopper optimization algorithm (Dinh, 2021a), gray wolf optimization (Daniel et al, 2017) and PSO (Tannaz et al, 2020) are a few further optimization methods that are currently in use. One recently proposed optimization algorithm is the CSA (Braik, 2021).…”

Section: Introductionmentioning

confidence: 99%

A Robust Medical Image Fusion Based on Synthetic Focusing Degree Criterion and Special Kernel Set for Clinical Diagnosis

Lepcha,

Goyal,

Dogra

et al. 2024

Journal of Computer Science

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Medical imaging has been widely used to diagnose diseases over the last two decades. Medical professionals still struggle to diagnose diseases using a single modality since there is a shortage of data in this domain. Therefore, images of specific organs with diseases from a variety of medical imaging systems can be combined using a technique called image fusion. Medical image fusion has prompted immense requisite applications in clinical applications in recent years. However, the fusion of medical images still facing a variety of challenges due to the input image quality. Protonema such as noise and low-contrast input medical images significantly reduces the quality of medical images. Still, recent image fusion methods are not significantly able to address the image quality problems. In order to address these problems, this study introduces a novel image fusion method that provides effective fusion performance even if the input images are noisy or low-contrast by combining the benefits of synthetic focusing degree criterion with a special kernel set. First, a Gaussian Curvature Filter (GCF) is used to sharpen the images in order to perform a Salient Feature Extraction (SFE). Then, we create a synthetic Focusing Degree Condition (FDC) that combines the Spatial Frequency (SF) and the Local Variance (LV) of the images to get the coarse fusion maps. The course fusion maps are then processed using median and morphological filters. The weighted fusion technology is used to generate the fused image. Finally, image enhancement is achieved by adding a special kernel to the fused image to obtain the final fusion result. Experimental results on the publicly available datasets exhibited that the proposed research article obtains the best results in terms of noisy and low-contrast medical images. Overall, it achieves significant performance both qualitatively and quantitively when compared to other competing state-of-the-art methods.

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Section: Introductionmentioning

confidence: 99%

A Robust Medical Image Fusion Based on Synthetic Focusing Degree Criterion and Special Kernel Set for Clinical Diagnosis

Lepcha,

Goyal,

Dogra

et al. 2024

Journal of Computer Science

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An agent-based heuristics optimisation model for production scheduling of make-to-stock connector plates manufacturing systems

Madi,

Al-Bazi,

Buckley

et al. 2023

Soft Comput

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The manufacturing systems’ success directly relates to their accurate, reliable and flexible schedules, including how production is planned and scheduled and which constraints are considered in generating the schedules. The study's objective arises from the need to generate an optimal production scheduling system in a connecting plates manufacturing company that works on a Make-To-Stock basis. This research investigates the impact of demand and operational constraints on production schedules, including the facility capacity, operators and machines availability, raw materials availability, inventory level and warehouse capacity. A multi-agent-based optimisation model is developed to face the complexity of considering demand and operational constraints and reflects their impact on generating a reliable production schedule. This model involves a proposed heuristic algorithm that considers demand and operations constraints in such a manufacturing environment and optimises the production schedule based on these restrictions/requirements. A real-life case study based on a connecting plates manufacturer company is used as a test bench of the proposed agent-based heuristic optimisation model. The proposed algorithm is compared with other related approaches to check its superiority based on key criteria, including inventory levels, missed/unsatisfied orders and total production time. Results show that the proposed heuristics algorithm reduced the number of missed orders by 34% compared with similar approaches.

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Medical image fusion based on transfer learning techniques and coupled neural P systems

Dinh,

Giang

2023

Neural Comput & Applic

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A Novel Approach Based on Marine Predators Algorithm for Medical Image Enhancement

Cited by 14 publications

References 63 publications

A Robust Medical Image Fusion Based on Synthetic Focusing Degree Criterion and Special Kernel Set for Clinical Diagnosis

A Robust Medical Image Fusion Based on Synthetic Focusing Degree Criterion and Special Kernel Set for Clinical Diagnosis

An agent-based heuristics optimisation model for production scheduling of make-to-stock connector plates manufacturing systems

Medical image fusion based on transfer learning techniques and coupled neural P systems

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