Abstract
This paper proposes an algorithm aimed at quantifying the expression of KI-67 protein in digital images of breast biopsy tissue samples obtained through an optical microscope. The algorithm allows to obtain a report on the quantity of non-proliferating and proliferating cells through the detection and quantification of KI-67. The sample analysis via software aims to reduce the level of subjectivity in the diagnosis of diseases such as breast cancer. The algorithm proposed involves the application of statistical image processing techniques, adaptive thresholds, object segmentation and color filtering. A method of analysis and quantification of overlapping cells is also proposed to improve the efficiency of the algorithm. The results of the method proposed were satisfactory, as they were highly correlated with those obtained by visual inspection by pathologists.
| Original language | English |
|---|---|
| Pages (from-to) | 201-211 |
| Number of pages | 11 |
| Journal | Advances in Science, Technology and Engineering Systems |
| Volume | 5 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2020 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Keywords
- Breast cancer
- Image processing
- Immunohistochemistry
- KI-67
Fingerprint
Dive into the research topics of 'An algorithm for automatic measurement of KI-67 proliferation index in digital images of breast tissue'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver