Name
Abstract | ||
|---|---|---|
Breast cancer has become one of the main causes of death among women in the many countries. The chances of patient survival can be considerably enhanced if breast tumors are identified at the earliest stage. In this study, we propose a cost effective and non-invasive detection technique, which is based on precision breast geometry, infrared breast temperature and inverse thermal modeling in order to prove that the inverse FEM is applicable for detection of the location and size of the tumor inside the breast. As a first step in this comprehensive study, we develop a novel and cost-effective experiment to obtain repeatable data for FEM validation, in which an artificial breast was 3D printed based on realistic breast geometry, tumors were simulated with heaters and thermograms of the breast were taken. Then forward thermal modeling was performed and validated with the experimental data. Furthermore, the effect of tumors on the thermal profile of the breast was examined by using both experimental and numerical approaches. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/BIBE.2018.00078 | 2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE) |
Keywords | Field | DocType |
FEM, breast tumor, thermal modeling, thermography | Thermography,Breast tumor,Experimental data,Breast cancer,Computer science,Algorithm,Finite element method,Artificial intelligence,Breast temperature,Machine learning | Conference |
ISSN | ISBN | Citations |
2159-5410 | 978-1-5386-5043-1 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olzhas Mukhmetov | 1 | 0 | 0.34 |
| Dastan Igali | 2 | 0 | 0.34 |
| Yong Zhao | 3 | 5 | 1.07 |
| S. C. Fok | 4 | 11 | 4.45 |
| Soo Lee Teh | 5 | 0 | 0.34 |
| Aigerim Mashekova | 6 | 0 | 0.34 |
| Ng Yin Kwee | 7 | 0 | 0.34 |