Name
Title | ||
|---|---|---|
Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer. |
Abstract | ||
|---|---|---|
•A novel image marker is developed for predicting the malignant lesion depicted on digital mammograms.•59 features are extracted from the whole breast area to generate the marker.•We initially demonstrate that the new marker enables to effectively distinguish the benign and malignant lesions. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.cmpb.2019.104995 | Computer Methods and Programs in Biomedicine |
Keywords | DocType | Volume |
Computer-aided diagnosis (CAD),Classification of mammograms,Quantitative image feature analysis,Support vector machine (SVM),Particle swarm optimization (PSO) algorithm | Journal | 179 |
ISSN | Citations | PageRank |
0169-2607 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuxin Chen | 1 | 0 | 0.34 |
| Abolfazl Zargari | 2 | 0 | 0.34 |
| Alan B. Hollingsworth | 3 | 0 | 1.01 |
| Hong Liu | 4 | 56 | 17.01 |
| Bin Zheng | 5 | 135 | 28.83 |
| yuchen qiu | 6 | 17 | 6.30 |