Evaluations on the Applicability of Generic and Modular Image Processing Chains for Quantitative 3D Data Analysis in Clinical Research and Radiographer Training

Abstract

The introduction of digital imaging and diagnostics facilities has fundamentally changed radiology. Nevertheless, theory of digital image processing and analysis as well as their practical application are still only a subsidiary part in nowadays radiology technician curricula. This work focuses on the evaluation, to what extent the authors' simplified and standardized process model for applying image processing modules in generic domains is suited for radiographer students and medical staff, lacking deeper theoretical knowledge compared to physicians and imaging experts. The semi-automated image processing workflow thereby comprises region growing, live-wire segmentation and filtering steps, all available from MeVisLab prototyping framework. It is shown that the proposed imaging chain is highly applicable for analysis and facilitating medical diagnostics of arbitrary anatomical structures from tomographic data. After compact practical instruction, radiographer students are versed to achieve complex 3D analysis perfectly suited for quantitative analysis in clinical research typically only achievable by use of specialized software.