Abstract
This publication presents an innovative method for analyzing, detecting, and predicting malignant cancer and metastasis through the integration of fractal vein pattern analysis, Chaos Game Representation (CGR), state-space models, and a hybrid Spiking Neural Network (SNN) / Convolutional Neural Network (CNN) architecture. This comprehensive approach is designed to address the challenges associated with detecting malignancies and predicting metastasis in medical images across various imaging modalities, focusing on the unique combination of advanced mathematical techniques and deep learning to refine and improve accuracy in cancer detection and prognosis
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Gagnon, Renee, "Integrated Method for Malignant Cancer Detection and Metastasis Prediction Using Fractal Vein Analysis, Deep Learning, and Multi-Modal Imaging", Technical Disclosure Commons, (August 14, 2024)
https://www.tdcommons.org/dpubs_series/7280