A software framework for diagnostic medical image perception with feedback, and a novel perception visualisation technique

Phillips, P W and Manning, D J and Donovan, T and Crawford, T and Higham, S (2005) A software framework for diagnostic medical image perception with feedback, and a novel perception visualisation technique. In: Medical Imaging 2005: Image Perception, Observer Performance, and Technology Assessment. SPIE-INT SOC OPTICAL ENGINEERING, San Diego, pp. 572-580. ISBN 0-8194-5723-X

Full text not available from this repository.

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.

Item Type:
Contribution in Book/Report/Proceedings
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/bf
Subjects:
?? PSYCHOLOGYBF PSYCHOLOGY ??
ID Code:
54504
Deposited By:
Deposited On:
24 May 2012 15:36
Refereed?:
Yes
Published?:
Published
Last Modified:
19 Sep 2023 03:17