Abstract
Intelligent medical systems based on supervised and unsupervised artificial neural networks are applied to the automatic visualization and classification of suspicious lesions in breast MRI. These systems represent an important component of future sophisticated computer-aided diagnosis systems and enable the extraction of spatial and temporal features of dynamic MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogenity of the cancerous tissue, these techniques reveal the malignant, benign and normal kinetic signals and and provide a regional subclassification of pathological breast tissue. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging.
| Original language | English |
|---|---|
| Title of host publication | Intelligent Computing: Theory and Applications IV, 2006, Orlando |
| Editors | K.L. Priddy, E. Ertin |
| Place of Publication | Bellingham |
| Publisher | SPIE |
| Pages | 38-49 |
| DOIs | |
| Publication status | Published - 2006 |
Publication series
| Name | Proceedings of SPIE |
|---|---|
| Volume | 6629 |
| ISSN (Print) | 0277-786X |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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