Creating Graph Abstractions for the Interpretation of Combined Functional and Anatomical Medical Images
Year: 2014
Type: conference-paper
Abstract: . The characteristics of the images produced by advanced scan-ning technologies has led to medical imaging playing a critical role in modern healthcare. The most advanced medical scanners combine dif-ferent modalities to produce multi-dimensional (3D/4D) complex data that is time-consuming and challenging interpret. The assimilation of these data is further compounded when multiple such images have to be compared, e.g., when assessing a patient’s response to treatment or re-sults from a clinical search engine. Abstract representations that present the important discriminating characteristics of the data have the poten-tial to prioritise the critical information in images and provide a more intuitive overview of the data, thereby increasing productivity when in-terpreting multiple complex medical images. Such abstractions act as a preview of the overall information and allow humans to decide when detailed inspection is necessary. Graphs are a natural method for ab-stracting medical images as they can represent the relationships between any pathology and the anatomical structures they affect. In this paper, we present a scheme for creating abstract graph visualisations that fa-cilitate an intuitive comparison of the anatomy-pathology relationships within complex medical images. The properties of our abstractions are derived from the characteristics of regions of interest (ROIs) within the images. We demonstrate how our scheme is used to preview, interpret, and compare the location of tumours within volumetric (3D) functional and anatomical images. Key words: graph abstractions, medical imaging, image interpretation, image comparison 1
Language: English
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2399151950