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Automatic reconstruction of overlapped cells in breast cancer FISH images
- Source :
- Expert Systems with Applications. 137:335-342
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- This paper presents a new image processing and analysis technique for the quality evaluation of cell nuclei to support medical diagnostics in breast cancer. The technique allows cell nuclei that are deformed or overlapped by biological material to be reconstructed. The paper proposes a sensitivity and similarity approach, enriching the PatchMatch correspondence algorithm in accurate cell reconstruction. Its application in reconstruction processes enables accelerated computations and an increased probability of obtaining appropriate segmentation results. The numerical results demonstrate that the developed system allows for automatic and effective cell nuclei reconstruction with an acceptable average area accuracy level above 85% compared with manual human results (assuming manual segmentation as a true value). The reconstruction system allows for the recovery of the proper shape of the analyzed distorted cells very rapidly and in a repeatable manner. An additional advantage of the procedure is that the nuclei area overlapped by artifacts or other cells can be determined. The experimental results prove the high utility of the method in final HER2 gene amplification assessment in breast cancer images.
- Subjects :
- 0209 industrial biotechnology
Similarity (geometry)
Computer science
business.industry
General Engineering
Pattern recognition
Image processing
02 engineering and technology
medicine.disease
Computer Science Applications
020901 industrial engineering & automation
Breast cancer
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
medicine
Fish
020201 artificial intelligence & image processing
Segmentation
Artificial intelligence
Sensitivity (control systems)
business
Subjects
Details
- ISSN :
- 09574174
- Volume :
- 137
- Database :
- OpenAIRE
- Journal :
- Expert Systems with Applications
- Accession number :
- edsair.doi...........cb447c33fe7292ce9b8852c34086e972