Advanced Analytical Methods for Multi-Spectral Transmission Imaging Optimization: Enhancing Breast Tissue Heterogeneity Detection and Tumor Screening with Hybrid Image Processing and Deep Learning DOI
Fulong Liu, Gang Li, Junqi Wang

et al.

Analytical Methods, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 15, 2024

This paper combines SPM, M_D-FA, and DLNM to improve multi-spectral image quality classify heterogeneities. Results show significant accuracy enhancements, achieving 95.47% with VGG19 98.47% ResNet101 in breast tumor screening.

Language: Английский

A Novel Diagnostic Framework for Breast Cancer: Combining Deep Learning with Mammogram-DBT Feature Fusion DOI Creative Commons
Nishu Gupta,

Jan Kubicek,

Marek Penhaker

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 103836 - 103836

Published: Dec. 1, 2024

Language: Английский

Citations

2
Early cancer detection using deep learning and medical imaging: A survey DOI Creative Commons
Istiak Ahmad, Fahad Alqurashi

Critical Reviews in Oncology/Hematology, Journal Year: 2024, Volume and Issue: 204, P. 104528 - 104528

Published: Oct. 15, 2024

Cancer, characterized by the uncontrolled division of abnormal cells that harm body tissues, necessitates early detection for effective treatment. Medical imaging is crucial identifying various cancers, yet its manual interpretation radiologists often subjective, labour-intensive, and time-consuming. Consequently, there a critical need an automated decision-making process to enhance cancer diagnosis. Previously, lot work was done on surveys different methods, most them were focused specific cancers limited techniques. This study presents comprehensive survey methods. It entails review 99 research articles collected from Web Science, IEEE, Scopus databases, published between 2020 2024. The scope encompasses 12 types cancer, including breast, cervical, ovarian, prostate, esophageal, liver, pancreatic, colon, lung, oral, brain, skin cancers. discusses techniques, medical data, image preprocessing, segmentation, feature extraction, deep learning transfer evaluation metrics. Eventually, we summarised datasets techniques with challenges limitations. Finally, provide future directions enhancing

Language: Английский

Citations

0
Advanced Analytical Methods for Multi-Spectral Transmission Imaging Optimization: Enhancing Breast Tissue Heterogeneity Detection and Tumor Screening with Hybrid Image Processing and Deep Learning DOI
Fulong Liu, Gang Li, Junqi Wang

et al.

Analytical Methods, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 15, 2024

This paper combines SPM, M_D-FA, and DLNM to improve multi-spectral image quality classify heterogeneities. Results show significant accuracy enhancements, achieving 95.47% with VGG19 98.47% ResNet101 in breast tumor screening.

Language: Английский

Citations

0