Name
Abstract | ||
|---|---|---|
Elasticity is an important indicator of tissue health, with increased stiffness pointing to an increased risk of cancer. We investigated a tissue inclusion characterization method for the application of early breast tumor identification. A tactile sensation imaging system (TSIS) is developed to capture images of the embedded lesions using total internal reflection principle. From tactile images, we developed a novel method to estimate that size, depth, and elasticity of the embedded lesion using 3-D finite-element-model-based forward algorithm, and neural-network-based inversion algorithm are employed. The proposed characterization method was validated by the realistic tissue phantom with inclusions to emulate the tumors. The experimental results showed that, the proposed characterization method estimated the size, depth, and Young's modulus of a tissue inclusion with 6.98%, 7.17%, and 5.07% relative errors, respectively. A pilot clinical study was also performed to characterize the lesion of human breast cancer patients using TSIS. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/JBHI.2013.2245142 | IEEE J. Biomedical and Health Informatics |
Keywords | Field | DocType |
tissue health indicator,biomechanics,realistic tissue phantom,tactile sensor,3d fem based forward algorithm,mechanical imaging,embedded lesion size,embedded lesion elasticity,embedded lesion depth,tissue inclusion characterization method,optical imaging,tsis,finite element model,tactile sensation imaging system,total internal reflection principle,tactile imaging system,embedded lesion images,cancer,embedded lesion characterization,biomedical imaging,finite element analysis,elasticity imaging,tactile sensors,neural network based inversion algorithm,tissue health elasticity,tumours,lesion young's modulus,elasticity,medical computing,tactile images,cancer risk,early breast tumor identification,phantoms,neural nets,young's modulus,tumor detection,algorithms,elastic modulus,young s modulus,imaging,artificial neural networks,finite element methods,algorithm design and analysis,sensors | Biomedical engineering,Breast cancer,Lesion,Medical imaging,Computer science,Imaging phantom,Artificial intelligence,Biomechanics,Pathology,Tactile sensor,Elasticity Imaging Techniques,Computer vision,Stiffness | Journal |
Volume | Issue | ISSN |
17 | 2 | 2168-2208 |
Citations | PageRank | References |
1 | 0.37 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jong-Ha Lee | 1 | 62 | 6.51 |
| Chang-Hee Won | 2 | 39 | 8.51 |