Ahmed Alksas

Orcid: 0000-0001-9409-931X

According to our database1, Ahmed Alksas authored at least 21 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Hybrid Deep Learning Approach with Feature Engineering for Enhanced Pulmonary Nodule Diagnosis.
SN Comput. Sci., October, 2024

Advanced OCTA imaging segmentation: Unsupervised, non-linear retinal vessel detection using modified self-organizing maps and joint MGRF modeling.
Comput. Methods Programs Biomed., 2024

Artificial Intelligence-Based Kidney Segmentation With Modified Cycle-Consistent Generative Adversarial Network and Appearance-Based Shape Prior.
IEEE Access, 2024

Optimizing Vertebral Lesion Diagnosis: A CAD-Driven Machine Learning Classification System With Multi-Modal MRI Texture Analysis.
IEEE Access, 2024

A Transfer Learning Framework for Lung Cancer Classification Using EfficientV2-L: Generalizability Assessment.
Proceedings of the 6th International Conference on Pattern Analysis and Intelligent Systems, 2024

A Neuroimaging ML-Based Framework for Anosmia Grading in Covid-19.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Retinal Vascular System Segmentation based on Non-Linear Map-Based Estimation of Joint MGRF Model.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Advancing Personalized Prostate Cancer Therapy Through Hormonal Treatment: Promising Findings.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
A novel higher order appearance texture analysis to diagnose lung cancer based on a modified local ternary pattern.
Comput. Methods Programs Biomed., October, 2023

Integrated Deep Learning and Stochastic Models for Accurate Segmentation of Lung Nodules From Computed Tomography Images: A Novel Framework.
IEEE Access, 2023

A Novel Technique of Pulmonary Nodules Auto Segmentation Using Modified Convolutional Neural Networks.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

An AI-Based CAP Framework for Wilms' Tumor Preoperative Chemotherapy Susceptibility.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

A Novel Textural and Morphological-Based CAD System for Early and Accurate Diagnosis of Vertebral Tumors.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Accurate Segmentation for Pathological Lung Based on Integration of 3D Appearance and Surface Models.
Proceedings of the IEEE International Conference on Image Processing, 2023

Early Diagnosis of Prostate Cancer Using Parametric Estimation of IVIM from DW-MRI.
Proceedings of the IEEE International Conference on Image Processing, 2023

Automated Diagnosis of Breast Cancer Using Deep Learning-Based Whole Slide Image Analysis of Molecular Biomarkers.
Proceedings of the IEEE International Conference on Image Processing, 2023

2022
A New Framework for Precise Identification of Prostatic Adenocarcinoma.
Sensors, 2022

A Comprehensive Non-invasive System for Early Grading of Gliomas.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

2021
A Comprehensive Computer-Assisted Diagnosis System for Early Assessment of Renal Cancer Tumors.
Sensors, 2021

A New Computer-Aided Diagnostic (Cad) System For Precise Identification Of Renal Tumors.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

2020
A Novel Computer-Aided Diagnostic System for Early Assessment of Hepatocellular Carcinoma.
Proceedings of the 25th International Conference on Pattern Recognition, 2020


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