Name
Abstract | ||
|---|---|---|
Brain tumors are the most common malignant neurologic tumors with the highest mortality and disability rate. Because of the delicate structure of the brain, the clinical use of several commonly used biopsy diagnosis is limited for brain tumors. Radiomics is an emerging technique for noninvasive diagnosis based on quantitative medical image analyses. However, current radiomics techniques are not st... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TMI.2017.2776967 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Feature extraction,Tumors,Dictionaries,Cancer,Estimation,Medical diagnostic imaging | Computer vision,Dictionary learning,Pattern recognition,Feature selection,Glioblastoma,Sparse approximation,Primary central nervous system lymphoma,Feature extraction,Redundancy (engineering),Artificial intelligence,Mathematics,Radiomics | Journal |
Volume | Issue | ISSN |
37 | 4 | 0278-0062 |
Citations | PageRank | References |
3 | 0.70 | 0 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guoqing Wu | 1 | 38 | 14.26 |
| Yin-Sheng Chen | 2 | 3 | 1.37 |
| Yuanyuan Wang | 3 | 28 | 11.12 |
| Jinhua Yu | 4 | 110 | 19.39 |
| Xiaofei Lv | 5 | 3 | 1.03 |
| Xue Ju | 6 | 3 | 0.70 |
| Zhifeng Shi | 7 | 5 | 1.41 |
| Liang Chen | 8 | 3 | 0.70 |
| Zhongping Chen | 9 | 3 | 1.03 |