Research output per year
Research output per year
Project Details
Description
The purpose of the project is to develop methods for performing automated cancer diagnoses in different types of histopathological images using use machine learning and medical image analysis. The aim is to improve standardization in performing cancer diagnoses in clinical practice. Methods have currently been developed mainly to detect cancer in histopathological images stained with hematoxylin and eosin (H&E).
| Short title | Digital Pathology |
|---|---|
| Status | Active |
| Effective start/end date | 01/12/2015 → … |
Keywords
- Artificial Neural Networks
- deep learning
- Machine learning
- cancer
- H&E
- IHC
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Automatic Bone Marrow Cellularity Estimation in H&E Stained Whole Slide Images
Nielsen, F. S., Pedersen, M. J., Olsen, M. V., Larsen, M. S., Røge, R. & Jørgensen, A. S., Oct 2019, In: Cytometry. Part A. 95, 10, p. 1066-1074 9 p.Research output: Contribution to journal › Journal article › Research › peer-review
8 Citations (Scopus) -
Quality assessment of Ki67 staining using cell line proliferation index and stain intensity features
Lanng, M. B., Møller, C. B., Andersen, A-S. H., Pálsdóttir, Á. A., Røge, R., Østergaard, L. R. & Jørgensen, A. S., Apr 2019, In: Cytometry. Part A : the journal of the International Society for Analytical Cytology. 95, 4, p. 381-388 8 p.Research output: Contribution to journal › Journal article › Research › peer-review
11 Citations (Scopus) -
Exploiting multiple color representations to improve colon cancer detection in whole slide H&E stains
Jørgensen, A. S., Emborg, J., Røge, R. & Østergaard, L. R., 2018, Computational Pathology and Ophthalmic Medical Image Analysis: First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, 16-20 September 2018, Proceedings. Taylor, Z., Bogunovic, H., Snead, D., Garvin, M. K., Chen, X. J., Ciompi, F., Xu, Y., Maier-Hein, L., Veta, M., Trucco, E., Stoyanov, D., Rajpoot, N., van der Laak, J., Martel, A. & McKenna, S. (eds.). Springer, p. 61-68 8 p. (Lecture Notes in Computer Science, Vol. 11039).Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
5 Citations (Scopus)
Equipment
Press/Media
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Kunstig intelligens kan snart hjælpe kræftpatienter
Lasse Riis Østergaard & Alex Skovsbo Jørgensen
04/07/2017
1 item of Media coverage
Press/Media: Press / Media