Background: This paper presents multilevel data glyphs optimized for the interactive knowledge discovery and visualization of large biomedical data sets. Data glyphs are three- dimensional objects defined by multiple levels of geometric descriptions (levels of detail) combined with a mapping of data attributes to graphical elements and methods, which specify their spatial position.
Methods: In the data mapping phase, which is done by a biomedical expert, meta information about the data attributes (scale, number of distinct values) are compared with the visual capabilities of the graphical elements in order to give a feedback to the user about the correctness of the variable mapping. The spatial arrangement of glyphs is done in a dimetric view, which leads to high data density, a simplified 3D navigation and avoids perspective distortion.
Results: We show the usage of data glyphs in the disease analyser a visual analytics application for personalized medicine and provide an outlook to a biomedical web visualization scenario.
Conclusions: Data glyphs can be successfully applied in the disease analyser for the analysis of big medical data sets. Especially the automatic validation of the data mapping, selection of subgroups within histograms and the visual comparison of the value distributions were seen by experts as an important functionality.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4158616 | PMC |
| http://dx.doi.org/10.1186/1471-2105-15-S6-S5 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Interactive mining of neural pathways to preoperative neurosurgical planning.
Comput Biol Med
January 2025
Medical Sciences School, Universidade Estadual de Campinas, R. Tessália Vieira de Camargo, 126, Campinas, 13083-887, São Paulo, Brazil; BRAINN Research, Innovation, and Dissemination Center, R. Vital Brasil, 251, Campinas, 13083-888, São Paulo, Brazil.
Background And Objective: Preoperative understanding of white matter anatomy, including its spatial relationship with pathology and superficial landmarks, is vital for effective surgical planning. The ability to interactively synthesize neural pathways from diffusion data and dynamically discern neuroanatomy-referenced fiber patterns enables neurosurgeons to construct detailed mental models of the patient's brain and assess surgical risks. We present a novel interactive software designed for real-time mining of neural pathways from diffusion-weighted magnetic resonance imaging (DW-MRI) data.
View Article and Find Full Text PDFAreas of interest (AOIs) are well-established means of providing semantic information for visualizing, analyzing, and classifying gaze data. However, the usual manual annotation of AOIs is time-consuming and further impaired by ambiguities in label assignments. To address these issues, we present an interactive labeling approach that combines visualization, machine learning, and user-centered explainable annotation.
View Article and Find Full Text PDFVisualization for Diagnostic Review of Copy Number Variants in Complex DNA Sequencing Data.
IEEE Trans Vis Comput Graph
April 2024
Genomics is at the core of precision medicine, and there are high expectations on genomics-enabled improvement of patient outcomes in the years to come. Around the world, initiatives to increase the use of DNA sequencing in clinical routine are being deployed, such as the use of broad panels in the standard care for oncology patients. Such a development comes at the cost of increased demands on throughput in genomic data analysis.
View Article and Find Full Text PDFReichsanzeiger-GT: An OCR ground truth dataset based on the historical newspaper "Deutscher Reichsanzeiger und Preußischer Staatsanzeiger" (German Imperial Gazette and Prussian Official Gazette) (1819-1945).
Data Brief
June 2024
University of Mannheim, University Library, Schloss Schneckenhof, 68161 Mannheim.
Reichsanzeiger-GT is a ground truth dataset for OCR training and evaluation based on the historical German newspaper "Deutscher Reichsanzeiger und Preußischer Staatsanzeiger" (German Imperial Gazette and Prussian Official Gazette), which was published from 1819 to 1945 and printed mostly in the typeface Fraktur (Black Letter). The dataset consists of 101 newspaper pages for the years 1820-1939, that cover a wide variety of topics, page layouts (lists, tables, and advertisements) as well as different typefaces. Using the transcription software Transkribus and the open-source OCR engine Tesseract we automatically created and manually corrected layout segmentations and transcriptions for each page, resulting in 65,563 text regions, 412 table regions, 119,429 text lines and 490,679 words.
View Article and Find Full Text PDFComputation of a probabilistic uranium concentration map of Norway: A digital expert elicitation approach employing random forests and artificial neural networks.
Heliyon
November 2023
Geological Survey of Norway (NGU), Leiv Eirikssons vei 39, 7040 Trondheim, Norway.
We compute the first probabilistic uranium concentration map of Norway. Such a map can support mineral exploration, geochemical mapping, or the assessment of the health risk to the human population. We employ multiple non-linear regression to fill the information gaps in sparse airborne and ground-borne uranium data sets.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!