5,544 research outputs found
Rapid Development of Medical Imaging Tools with Open-Source Libraries
Rapid prototyping is an important element in researching new imaging analysis techniques and developing custom medical applications. In the last ten years, the open source community and the number of open source libraries and freely available frameworks for biomedical research have grown significantly. What they offer are now considered standards in medical image analysis, computer-aided diagnosis, and medical visualization. A cursory review of the peer-reviewed literature in imaging informatics (indeed, in almost any information technology-dependent scientific discipline) indicates the current reliance on open source libraries to accelerate development and validation of processes and techniques. In this survey paper, we review and compare a few of the most successful open source libraries and frameworks for medical application development. Our dual intentions are to provide evidence that these approaches already constitute a vital and essential part of medical image analysis, diagnosis, and visualization and to motivate the reader to use open source libraries and software for rapid prototyping of medical applications and tools
Veni Vidi Vici, A Three-Phase Scenario For Parameter Space Analysis in Image Analysis and Visualization
Automatic analysis of the enormous sets of images is a critical task in life
sciences. This faces many challenges such as: algorithms are highly
parameterized, significant human input is intertwined, and lacking a standard
meta-visualization approach. This paper proposes an alternative iterative
approach for optimizing input parameters, saving time by minimizing the user
involvement, and allowing for understanding the workflow of algorithms and
discovering new ones. The main focus is on developing an interactive
visualization technique that enables users to analyze the relationships between
sampled input parameters and corresponding output. This technique is
implemented as a prototype called Veni Vidi Vici, or "I came, I saw, I
conquered." This strategy is inspired by the mathematical formulas of numbering
computable functions and is developed atop ImageJ, a scientific image
processing program. A case study is presented to investigate the proposed
framework. Finally, the paper explores some potential future issues in the
application of the proposed approach in parameter space analysis in
visualization
Health Figures: An Open Source JavaScript Library for Health Data Visualization
The way we look at data has a great impact on how we can understand it,
particularly when the data is related to health and wellness. Due to the
increased use of self-tracking devices and the ongoing shift towards preventive
medicine, better understanding of our health data is an important part of
improving the general welfare of the citizens. Electronic Health Records,
self-tracking devices and mobile applications provide a rich variety of data
but it often becomes difficult to understand. We implemented the hFigures
library inspired on the hGraph visualization with additional improvements. The
purpose of the library is to provide a visual representation of the evolution
of health measurements in a complete and useful manner. We researched the
usefulness and usability of the library by building an application for health
data visualization in a health coaching program. We performed a user evaluation
with Heuristic Evaluation, Controlled User Testing and Usability
Questionnaires. In the Heuristics Evaluation the average response was 6.3 out
of 7 points and the Cognitive Walkthrough done by usability experts indicated
no design or mismatch errors. In the CSUQ usability test the system obtained an
average score of 6.13 out of 7, and in the ASQ usability test the overall
satisfaction score was 6.64 out of 7. We developed hFigures, an open source
library for visualizing a complete, accurate and normalized graphical
representation of health data. The idea is based on the concept of the hGraph
but it provides additional key features, including a comparison of multiple
health measurements over time. We conducted a usability evaluation of the
library as a key component of an application for health and wellness
monitoring. The results indicate that the data visualization library was
helpful in assisting users in understanding health data and its evolution over
time.Comment: BMC Medical Informatics and Decision Making 16.1 (2016
Open source bioimage informatics for cell biology
Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery
TopicViz: Semantic Navigation of Document Collections
When people explore and manage information, they think in terms of topics and
themes. However, the software that supports information exploration sees text
at only the surface level. In this paper we show how topic modeling -- a
technique for identifying latent themes across large collections of documents
-- can support semantic exploration. We present TopicViz, an interactive
environment for information exploration. TopicViz combines traditional search
and citation-graph functionality with a range of novel interactive
visualizations, centered around a force-directed layout that links documents to
the latent themes discovered by the topic model. We describe several use
scenarios in which TopicViz supports rapid sensemaking on large document
collections
XML in Motion from Genome to Drug
Information technology (IT) has emerged as a central to the solution of contemporary genomics and drug discovery problems. Researchers involved in genomics, proteomics, transcriptional profiling, high throughput structure determination, and in other sub-disciplines of bioinformatics have direct impact on this IT revolution. As the full genome sequences of many species, data from structural genomics, micro-arrays, and proteomics became available, integration of these data to a common platform require sophisticated bioinformatics tools. Organizing these data into knowledgeable databases and developing appropriate software tools for analyzing the same are going to be major challenges. XML (eXtensible Markup Language) forms the backbone of biological data representation and exchange over the internet, enabling researchers to aggregate data from various heterogeneous data resources. The present article covers a comprehensive idea of the integration of XML on particular type of biological databases mainly dealing with sequence-structure-function relationship and its application towards drug discovery. This e-medical science approach should be applied to other scientific domains and the latest trend in semantic web applications is also highlighted
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