Cited by An Extensive Analysis of Amphibious Drones for Surveillance

Advanced Medical Image Segmentation Enhancement: A Particle-Swarm-Optimization-Based Histogram Equalization Approach DOI

Shoffan Saifullah, Rafał Dreżewski

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(2), P. 923 - 923

Published: Jan. 22, 2024

Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy particle swarm optimization (PSO) combined with histogram equalization (HE) preprocessing segmentation, focusing on lung CT scan chest X-ray datasets. Best-cost values reveal PSO algorithm’s performance, HE demonstrating significant stabilization enhanced convergence, particularly complex images. Evaluation metrics, including accuracy, precision, recall, F1-score/Dice, specificity, Jaccard, show substantial improvements preprocessing, emphasizing its impact accuracy. Comparative analyses against alternative methods, such as Otsu, Watershed, K-means, confirm competitiveness PSO-HE approach, especially The also underscores positive influence clarity precision. These findings highlight promise approach advancing accuracy reliability pave way further method integration to enhance this critical healthcare application.

Language: Английский

Citations

Design of Cost Efficient VBIR Technique Using ICA and IVCA DOI

B. P. Pradeep Kumar,

N. N. Srinidhi,

S. L. Shiva Darshan

et al.

SN Computer Science, Journal Year: 2024, Volume and Issue: 5(5)

Published: May 17, 2024

Abstract With an emphasis on early-stage contrast agent transit through tumour vasculature, this study presents Adaptive Complex Independent Components Analysis (ACICA) as a unique method for evaluating intravascular responsiveness in prostatic tissue. Furthermore, new SVM clustering is introduced that outperforms the conventional k-means image retrieval based vision. The emphasises how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may be improved conjunction with quantitative analysis. Within field of DCE-MRI, ACICA stands out attention measurer. Utilising spatial independence extravascular and (MR) data, offers strong foundation DCE-MRI It incorporates pharmacokinetic modelling to optimise time lag, especially useful arterial curves, reference region (RR)-based technique adjust concentration curve. model's evaluation yields outstanding results, recall accuracy ranging from 83 99% 82.8% 99.6%, respectively. average precision across datasets are 92.86% 92.82%).All things considered, demonstrates effectiveness viable paths enhancing clinical results diagnostic treatment prostate cancer.

Language: Английский

Citations

Robust Automatic Speech Recognition Using Wavelet-Based Adaptive Wavelet Thresholding: A Review DOI

Mahadevaswamy Shanthamallappa,

Kiran Kiran,

Naveen Kumar H N

et al.

SN Computer Science, Journal Year: 2024, Volume and Issue: 5(2)

Published: Feb. 1, 2024

Language: Английский

Citations

Advanced Medical Image Segmentation Enhancement: A Particle Swarm Optimization-Based Histogram Equalization Approach DOI

Shoffan Saifullah, Rafał Dreżewski

Published: Jan. 2, 2024

Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study on the efficacy of Particle Swarm Optimization (PSO) combined with Histogram Equalization (HE) preprocessing segmentation, focusing Lung CT-Scan Chest X-ray datasets. Best Cost values reveal PSO algorithm’s performance, HE demonstrating significant stabilization enhanced convergence, particularly complex images. Evaluation metrics, including Accuracy, Precision, Recall, F-Score, Specificity, Dice, Jaccard, show substantial improvements preprocessing, emphasizing its impact accuracy. Comparative analyses against alternative methods, such as Otsu, Watershed, K-means, confirm competitiveness PSO-HE approach, especially The also underscores positive influence clarity precision. These findings highlight promise approach advancing accuracy reliability paving way further method integration to enhance this critical healthcare application.

Language: Английский

Citations

Vbir-Based Assessment of Radiographic-Divergence Agent Attention in Prostate Melanoma Patients DOI

Pramod Rangaiah, Pradeep Kumar, Robin Augustine

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

Histopathology-driven prostate cancer identification: A VBIR approach with CLAHE and GLCM insights DOI

Pramod Rangaiah, B. P. Pradeep Kumar, Robin Augustine

et al.

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 182, P. 109213 - 109213

Published: Oct. 2, 2024

Language: Английский

Citations

Enhanced Glaucoma Detection Using U-Net and U-Net+ Architectures Using Deep Learning Techniques DOI

Pradeep Kumar, Pramod Rangaiah, Robin Augustine

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

Enhanced perceptual wavelet packet features for spontaneous Kannada sentence recognition under uncontrolled conditions DOI

Mahadevaswamy Shanthamallappa, B. P. Pradeep Kumar

International Journal of Speech Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 25, 2025

Language: Английский

Citations

Precision diagnosis of burn injuries using imaging and predictive modeling for clinical applications DOI

Pramod Rangaiah, B. P. Pradeep Kumar, Fredrik Huss

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 4, 2025

Burns represents a serious clinical problem because the diagnosis and assessment are very complex. This paper proposes methodology that combines use of advanced medical imaging with predictive modeling for improvement burn injury assessment. The proposed framework makes Adaptive Complex Independent Components Analysis (ACICA) Reference Region (TBSA) methods in conjunction deep learning techniques precise estimation depth Total Body Surface Area analysis. It also allows burns high accuracy, calculation TBSA, non-invasive analysis 96.7% accuracy using an RNN model. Extensive experimentation on DCE-LUV samples validates enhanced diagnostic precision detailed texture These technologies provide nuanced insights into severity, improving treatment planning. Our results demonstrate potential these to revolutionize care optimize patient outcomes.

Language: Английский

Citations

The Burn Grafting Image Reclamation Redefined with the Peak-Valley Approach DOI

B. P. Pradeep Kumar,

E. Naresh,

A. Ashwitha

et al.

Critical Reviews in Biomedical Engineering, Journal Year: 2025, Volume and Issue: 53(2), P. 21 - 35

Published: Jan. 1, 2025

Burn injuries constitute a significant public health challenge, often necessitating the expertise of medical professionals for diagnosis. However, in scenarios where specialized facilities are unavailable, utility automated burn assessment tools becomes evident. Factors such as area, depth, and location play pivotal role determining severity. In this study, we present classification model diagnosis, leveraging machine learning techniques. Our approach includes an image reclamation system that incorporates peak valley algorithm, ensuring removal noise while consistently delivering high-quality results. By using skewness kurtosis, demonstrate substantial improvements diagnostic accuracy. proposed sources key features from enhanced grafting samples transformation, enabling computation BQs unique bin analysis to enhance reclamation. experimental results highlight efficiency gains, notably growing matching graft 14 images. The intended work involves creation model. utilizes support vector (SVM). evaluation will be conducted untrained catalogue, with specific focus on its effectiveness reclaiming images necessitate grafts distinguishing them those do not. holds promise sample emergency settings, thereby expediting more accurate diagnoses treatments acute injuries. This has latent save lives improve patient upshots traumas.

Language: Английский

Citations