Abstract
| 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 |
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Visualization of Suspicious Lesions in Breast MRI Based on Intelligent Neural Systems. / Twellmann, T.; Lange, O.; Nattkemper, T.W.; Meyer-Bäse, A.
Intelligent Computing: Theory and Applications IV, 2006, Orlando. ed. / K.L. Priddy; E. Ertin. Bellingham : SPIE, 2006. p. 38-49 (Proceedings of SPIE; Vol. 6629).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Visualization of Suspicious Lesions in Breast MRI Based on Intelligent Neural Systems
AU - Twellmann, T.
AU - Lange, O.
AU - Nattkemper, T.W.
AU - Meyer-Bäse, A.
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
U2 - 10.1117/12.668674
DO - 10.1117/12.668674
M3 - Conference contribution
T3 - Proceedings of SPIE
SP - 38
EP - 49
BT - Intelligent Computing: Theory and Applications IV, 2006, Orlando
A2 - Priddy, K.L.
A2 - Ertin, E.
PB - SPIE
CY - Bellingham
ER -