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Proceedings Paper

A software framework for diagnostic medical image perception with feedback and a novel perception visualization technique
Author(s): Peter W. Phillips; David J. Manning; Tim Donovan; Trevor Crawford; Stephen Higham
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Paper Abstract

This paper describes a software framework and analysis tool to support the collection and analysis of eye movement and perceptual feedback data for a variety of diagnostic imaging modalities. The framework allows the rapid creation of experiment software that can display a collection of medical images of a particular modality, capture eye trace data, and record marks added to an image by the observer, together with their final decision. There are also a number of visualisation techniques for the display of eye trace information. The analysis tool supports the comparison of individual eye traces for a particular observer or traces from multiple observers for a particular image. Saccade and fixation data can be visualised, with user control of fixation identification functions and properties. Observer markings are displayed, and predefined regions of interest are supported. The software also supports some interactive and multi-image modalities. The analysis tool includes a novel visualisation of scan paths across multi-image modalities. Using an exploded 3D view of a stack of MRI scan sections, an observer's scan path can be shown traversing between images, in addition to inspecting them.

Paper Details

Date Published: 6 April 2005
PDF: 9 pages
Proc. SPIE 5749, Medical Imaging 2005: Image Perception, Observer Performance, and Technology Assessment, (6 April 2005); doi: 10.1117/12.595365
Show Author Affiliations
Peter W. Phillips, Lancaster Univ. (United Kingdom)
David J. Manning, St. Martin's College (United Kingdom)
Tim Donovan, St. Martin's College (United Kingdom)
Trevor Crawford, Lancaster Univ. (United Kingdom)
Stephen Higham, Lancaster Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 5749:
Medical Imaging 2005: Image Perception, Observer Performance, and Technology Assessment
Miguel P. Eckstein; Yulei Jiang, Editor(s)

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