An Effective Segmentation of MRI Images Combining Threshold and Hybrid Particle Swarm Optimization (HPSO-T) for Lung, Bone and Brain (LBB) DOI Open Access

N Raghapriya,

N Aswini,

G. Savitha

et al.

International Journal of Electronics and Communication Engineering, Journal Year: 2024, Volume and Issue: 11(12), P. 92 - 99

Published: Dec. 31, 2024

Segmentation in medical imaging is one of the fundamental problems image processing. Perceptual completion and recognition during picture segmentation are issues with segmentation. Machine vision-based threshold an essential detecting tool. The issue time consumption arises traditional method. However, optimization techniques can help to resolve these problems. An effective technique needed determine ideal threshold. thresholding will become more computationally intensive increasing thresholds. This research proposed Hybrid Particle Swarm Optimization Thresholding (HPSO-T) used for assess MRI Image managing various tumors Lung, Brain Bone-(LBB). work extracts scan pictures using LBB data acquired from Kaggle website. suggested methodology outperforms other two approaches market a Dice Index 0.93.

Language: Английский

Modified U-Net with attention gate for enhanced automated brain tumor segmentation DOI
Shoffan Saifullah, Rafał Dreżewski, Anton Yudhana

et al.

Neural Computing and Applications, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Language: Английский

Citations

1
Improved Brain Tumor Segmentation Using Modified U-Net based on Particle Swarm Optimization Image Enhancement DOI
Shoffan Saifullah, Rafał Dreżewski

Proceedings of the Genetic and Evolutionary Computation Conference Companion, Journal Year: 2024, Volume and Issue: unknown, P. 611 - 614

Published: July 14, 2024

Language: Английский

Citations

8
Automatic Brain Tumor Segmentation Using Convolutional Neural Networks: U-Net Framework with PSO-Tuned Hyperparameters DOI
Shoffan Saifullah, Rafał Dreżewski

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 333 - 351

Published: Jan. 1, 2024

Language: Английский

Citations

5
Advanced brain tumor segmentation using DeepLabV3Plus with Xception encoder on a multi-class MR image dataset DOI
Shoffan Saifullah, Rafał Dreżewski, Anton Yudhana

et al.

Multimedia Tools and Applications, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 21, 2025

Language: Английский

Citations

0
ViT-CB: Integrating hybrid Vision Transformer and CatBoost to enhanced brain tumor detection with SHAP DOI
Radius Tanone, Li-Hua Li, Shoffan Saifullah

et al.

Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 100, P. 107027 - 107027

Published: Oct. 24, 2024

Language: Английский

Citations

3
Wavelet Guided Visual State Space Model and Patch Resampling Enhanced U-shaped Structure for Skin Lesion Segmentation DOI Creative Commons

Shuwan Feng,

Xiaowei Chen, Shengzhi Li

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 181521 - 181532

Published: Jan. 1, 2024

Language: Английский

Citations

1
Nonlinear crossing strategy-based particle swarm optimizations with time-varying acceleration coefficients DOI Creative Commons

Keigo Watanabe,

Xiongshi Xu

Applied Intelligence, Journal Year: 2024, Volume and Issue: 54(13-14), P. 7229 - 7277

Published: June 3, 2024

Abstract In contemporary particle swarm optimization (PSO) algorithms, to efficiently explore global optimum solutions, it is common practice set the inertia weight monotonically decrease over time for stability, while allowing two acceleration coefficients, representing cognitive and social factors, adopt decreasing or increasing functions time, including random variations. However, there has been little discussion on a unified design approach these time-varying coefficients. This paper presents methodology designing monotonic construct nonlinear coefficients in PSO, along with control strategy exploring solutions. We first by linearly amplifying well-posed that increase normalized time. Here, ensure satisfaction of specified conditions at initial terminal points search process. many employed thus far only satisfy well-posedness either prompting proposal method adjust them virtually meet points. Furthermore, we propose crossing where developed intersect within interval, effectively guiding process pre-determining values times. The performance our Nonlinear Crossing Strategy-based Particle Swarm Optimization (NCS-PSO) evaluated using CEC2014 (Congress Evolutionary Computation 2014) benchmark functions. Through comprehensive numerical comparisons statistical analyses, demonstrate superiority seven conventional algorithms. Additionally, validate approach, particularly drone navigation scenario, through an example optimal 3D path planning. These contributions advance field PSO techniques, providing robust addressing complex problems.

Language: Английский

Citations

0
Semi-Supervised and Class-Imbalanced Open Set Medical Image Recognition DOI Creative Commons

Yiqian Xu,

Ruofan Wang, Rui-Wei Zhao

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 122852 - 122877

Published: Jan. 1, 2024

Language: Английский

Citations

0
Improving YOLOv8 Performance Using Hyperparameter Optimization with Gray Wolf Optimizer to Detect Acute Lymphoblastic Leukemia DOI
Tanzilal Mustaqim, Chastine Fatichah, Nanik Suciati

et al.

Published: Sept. 12, 2024

Language: Английский

Citations

0
An Effective Segmentation of MRI Images Combining Threshold and Hybrid Particle Swarm Optimization (HPSO-T) for Lung, Bone and Brain (LBB) DOI Open Access

N Raghapriya,

N Aswini,

G. Savitha

et al.

International Journal of Electronics and Communication Engineering, Journal Year: 2024, Volume and Issue: 11(12), P. 92 - 99

Published: Dec. 31, 2024

Segmentation in medical imaging is one of the fundamental problems image processing. Perceptual completion and recognition during picture segmentation are issues with segmentation. Machine vision-based threshold an essential detecting tool. The issue time consumption arises traditional method. However, optimization techniques can help to resolve these problems. An effective technique needed determine ideal threshold. thresholding will become more computationally intensive increasing thresholds. This research proposed Hybrid Particle Swarm Optimization Thresholding (HPSO-T) used for assess MRI Image managing various tumors Lung, Brain Bone-(LBB). work extracts scan pictures using LBB data acquired from Kaggle website. suggested methodology outperforms other two approaches market a Dice Index 0.93.

Language: Английский

Citations

0