Demo Data from EDBT 2026 / reviewers in the wild / expert
U. Adiga
dblp:35/6784
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2006
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 67% Bioinformatics and computational biology · 33% | |
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics
computational pathology |
0.1 | 1 | 2006 | High-throughput analysis of multispectral images of breast cancer tissue · IEEE Trans. Image Process. 2006 |
Bioinformatics and computational biology › bioimage informatics
high-throughput image analysis |
0.1 | 1 | 2006 | High-throughput analysis of multispectral images of breast cancer tissue · IEEE Trans. Image Process. 2006 |
Medical and health informatics › computational pathology
nuclei segmentation |
0.1 | 1 | 2006 | High-throughput analysis of multispectral images of breast cancer tissue · IEEE Trans. Image Process. 2006 |
Image and video processing
image segmentation |
0.0 | 1 | 2006 | High-throughput analysis of multispectral images of breast cancer tissue · IEEE Trans. Image Process. 2006 |
Methods — techniques the papers use, named apart from their topics
shrink-wrap operation · 0.1directional diffusion · 0.1beltrami flow-based reaction-diffusion · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | High-throughput analysis of multispectral images of breast cancer tissueabstractStatistical analysis of genetic changes within cell nuclei that are far from the primary tumor would help determine whether such changes have occurred prior to tumor invasion. To determine whether the gene amplification in cells is morphologically and/or genetically related to the primary tumor requires quantitative evaluation of a large number of cell nuclei from continuous meaningful structures such as milk-ducts, tumors, etc., located relatively far from the primary tumor. To address this issue, we have designed an integrated image analysis software system for high-throughput segmentation of nuclei. Filters such as Beltrami flow-based reaction-diffusion, directional diffusion, etc., were used to pre-process the images resulting in a better segmentation. The accurate shape of the segmented nucleus was recovered using an iterative "shrink-wrap" operation. The study of two cases of ductal carcinoma in situ in breast tissue supports the biological observation regarding the existence of a preferential intraductal invasion, and therefore a common origin, between the primary tumor and the gene amplification in the cell-nuclei lining the ductal structures in the breast. U. Adiga, Ravi Malladi, Rodrigo Fernandez-Gonzalez, Carlos Ortiz-de-Solorzano |
IEEE Trans. Image Process. | 1 |