Name
Abstract | ||
|---|---|---|
Analysis of histopathological images covers a wide field of clinical practice in different pathological conditions. In many cases, biopsy images from different sources share similar characteristics. In this work, a method for image enhancement of biopsy images is proposed. During the first stage, the quality of the image is optimized, while in the second stage, a clustering technique is employed to separate the tissue from the background. For the evaluation of the method, Liver biopsies which have been extracted for the staging of Hepatitis C, are employed. The methodology has been tested using 19 liver biopsy images from patients who suffer from hepatic fibrosis and steatosis, obtaining detection Accuracy over 97% in pixel level. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/BIBE.2017.00-49 | 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) |
Keywords | Field | DocType |
tissue detection,liver biopsy,image analysis | Fibrosis,Computer science,Medical imaging,Liver biopsy,Hepatitis C,Biopsy,Image segmentation,Pixel,Bioinformatics,Radiology,Stage (cooking) | Conference |
ISSN | ISBN | Citations |
2471-7819 | 978-1-5386-1325-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolaos Giannakeas | 1 | 43 | 12.59 |
| Maria Tsiplakidou | 2 | 0 | 0.68 |
| Markos G. Tsipouras | 3 | 372 | 30.51 |
| Pinelopi Manousou | 4 | 4 | 2.72 |
| Roberta Forlano | 5 | 0 | 0.68 |
| Alexandros T. Tzallas | 6 | 225 | 27.88 |