Name
Title | ||
|---|---|---|
Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome. |
Abstract | ||
|---|---|---|
BackgroundTo investigate the feasibility of automated segmentation of visceral and subcutaneous fat areas from computed tomography (CT) images of ovarian cancer patients and applying the computed adiposity-related image features to predict chemotherapy outcome. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12880-016-0157-5 | BMC Medical Imaging |
Keywords | Field | DocType |
Computer-aided detection (CAD), Quantitative image feature analysis, Prediction of chemotherapy outcome, Clinical image markers for cancer prognosis prediction | Segmentation,Computer-aided,Feature (computer vision),Chemotherapy,Computed tomography,Radiography,Ovarian cancer,Radiology,Medicine,Pathology | Journal |
Volume | Issue | ISSN |
16 | 1 | 1471-2342 |
Citations | PageRank | References |
3 | 0.52 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunzhi Wang | 1 | 18 | 1.97 |
| yuchen qiu | 2 | 17 | 6.30 |
| theresa thai | 3 | 9 | 3.08 |
| kathleen n moore | 4 | 9 | 2.74 |
| Hong Liu | 5 | 56 | 17.01 |
| Bin Zheng | 6 | 163 | 19.84 |