T
T. Goudas
Researcher at University of Central Greece
Publications - 7
Citations - 90
T. Goudas is an academic researcher from University of Central Greece. The author has contributed to research in topics: Image segmentation & Feature extraction. The author has an hindex of 4, co-authored 7 publications receiving 79 citations. Previous affiliations of T. Goudas include University of Piraeus.
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Journal ArticleDOI
Ratsnake: a versatile image annotation tool with application to computer-aided diagnosis.
TL;DR: Ratsnake is presented, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system.
Proceedings ArticleDOI
Fisheye camera modeling for human segmentation refinement in indoor videos
TL;DR: The constructed camera model is utilized to achieve a simple geometric reasoning that corrects gaps and mistakes of the human figure segmentation, and enables the inference of possible real world positions of a segmented cluster of pixels in the video frame.
Journal ArticleDOI
A Collaborative Biomedical Image-Mining Framework: Application on the Image Analysis of Microscopic Kidney Biopsies
TL;DR: An application, exploiting web services and applying ontological modeling, is presented, to enable the intelligent creation of image-mining workflows and a case study dealing with the creation of a sample workflow for the analysis of kidney biopsy microscopy images is presented.
Proceedings ArticleDOI
An open data mining framework for the analysis of medical images: Application on Obstructive Nephropathy microscopy images
Charalampos Doukas,T. Goudas,Simon Fischer,Ingo Mierswa,Aristotle Chatziioannou,Ilias Maglogiannis +5 more
TL;DR: An open image-mining framework that provides access to tools and methods for the characterization of medical images is presented and initial classification results are quite promising demonstrating the feasibility of automated characterization of kidney biopsy images.
Proceedings ArticleDOI
Human segmentation and pose recognition in fish-eye video for assistive environments
TL;DR: This work presents a system, which uses computer vision techniques for human silhouette segmentation from video in indoor environments and a parametric 3D human model, in order to recognize the posture of the monitored person.