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U. Adiga

dblp:35/6784 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Medical and health informatics
computational pathology
0.112006
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
0.112006
High-throughput analysis of multispectral images of breast cancer tissue · IEEE Trans. Image Process. 2006
Medical and health informatics › computational pathology
nuclei segmentation
0.112006
High-throughput analysis of multispectral images of breast cancer tissue · IEEE Trans. Image Process. 2006
Image and video processing
image segmentation
0.012006
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
YearPublicationVenuePosition
2006 High-throughput analysis of multispectral images of breast cancer tissue
abstract
Statistical 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