Name
Abstract | ||
|---|---|---|
•Adrenal tumors can be adherent to liver, spleen, spinal cord, kidney, and this situation prevents an accurate segmentation of adrenal tumors.•In addition, low contrast, non-standardized shape and size, homogeneity, and heterogeneity of the tumors are considered as problems in segmentation.•This study proposes a computer-aided diagnosis (CAD) system to segment adrenal tumors by eliminating the above problems.•The performance of the proposed method was assessed on 113 Magnetic Resonance (MR) images using seven statistical metrics.•As a result, an efficient framework is presented on segmentation of adrenal tumors for MR images, especially for cyst-based tumors. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cmpb.2018.07.009 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Adrenal tumor segmentation,CAD system,Hybrid approach,MR images | Active contour model,Computer vision,Sørensen–Dice coefficient,Segmentation,Computer science,Image processing,Adaptive histogram equalization,Artificial intelligence,Region growing,Radiology,Thresholding,Magnetic resonance imaging | Journal |
Volume | ISSN | Citations |
164 | 0169-2607 | 0 |
PageRank | References | Authors |
0.34 | 10 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mücahid Barstugan | 1 | 0 | 0.34 |
| Rahime Ceylan | 2 | 259 | 17.10 |
| Semih Asoglu | 3 | 0 | 0.68 |
| Hakan Cebeci | 4 | 0 | 0.68 |
| Mustafa Koplay | 5 | 0 | 1.01 |