Name
Title | ||
|---|---|---|
Novel Morphological Features for Non-mass-like Breast Lesion Classification on DCE-MRI. |
Abstract | ||
|---|---|---|
For both visual analysis and computer assisted diagnosis systems in breast MRI reading, the delineation and diagnosis of ductal carcinoma in situ ( DCIS) is among the most challenging tasks. Recent studies show that kinetic features derived from dynamic contrast enhanced MRI (DCE-MRI) are less effective in discriminating malignant non-masses against benign ones due to their similar kinetic characteristics. Adding shape descriptors can improve the differentiation accuracy. In this work, we propose a set of novel morphological features using the sphere packing technique, aiming to discriminate non-masses based on their shapes. The feature extraction, selection and the classification modules are integrated into a computer-aided diagnosis ( CAD) system. The evaluation was performed on a data set of 106 non-masses extracted from 86 patients, which achieved an accuracy of 90.56 %, precision of 90.3%, and area under the receiver operating characteristic (ROC) curve (AUC) of 0.94 for the differentiation of benign and malignant types. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-47157-0_37 | Lecture Notes in Computer Science |
DocType | Volume | ISSN |
Conference | 10019 | 0302-9743 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad Razavi | 1 | 2 | 1.06 |
| Lei Wang | 2 | 0 | 0.68 |
| Tao Tan | 3 | 46 | 10.25 |
| Nico Karssemeijer | 4 | 992 | 122.49 |
| Lars Linsen | 5 | 280 | 45.80 |
| Udo Frese | 6 | 629 | 55.63 |
| Horst K. Hahn | 7 | 450 | 72.61 |
| Gabriel Zachmann | 8 | 636 | 60.39 |