Anca Dima

dblp:56/1937 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2002
—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
Bioinformatics and computational biology · 100%
Computer graphics and multimedia
1 paper
Image and video processing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › bioimage informatics › bioimage analysis
microscopy image analysis
0.012002
Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform · IEEE Trans. Image Process. 2002
Bioinformatics and computational biology › bioimage informatics › cell segmentation
neuron segmentation
0.012002
Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform · IEEE Trans. Image Process. 2002
Image and video processing › edge detection
multiscale edge detection
0.012002
Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform · IEEE Trans. Image Process. 2002

Methods — techniques the papers use, named apart from their topics

multiscale edges · 0.13d wavelet transform · 0.03-d wavelet transform · 0.0
YearPublicationVenuePosition
2002 Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform
abstract
In this work, we focus on methods for the preprocessing of neurons from three-dimensional (3-D) confocal microscopy images, which are needed for a subsequent detailed morphologic analysis. Due to the specific image properties of confocal microscopy scans, we had to include several heuristic approaches which are based on multiscale edges to guarantee meaningful results: (1) a reliable segmentation of objects of different sizes independent of image contrast, and, based on it, (2) the computation of skeleton points along the branch central axes, and (3) the reliable detection of branching points and of problematic regions. These are preprocessing steps to gather information which is needed by the subsequent construction of a graph representing the geometry of the neuron and a final surface reconstruction.
Anca Dima, Michael Scholz 0003, Klaus Obermayer
IEEE Trans. Image Process.1