The use of a channelization mechanism on model observers not only makes mimicking human visual behavior possible, but also reduces the amount of image data needed to estimate the model observer parameters. The channelized Hotelling observer (CHO) and channelized scanning linear observer (CSLO) have recently been used to assess CT image quality for detection tasks and combined detection/estimation tasks, respectively. Although the use of channels substantially reduces the amount of data required to compute image quality, the number of scans required for CT imaging is still not practical for routine use. It is our desire to further reduce the number of scans required to make CHO or CSLO an image quality tool for routine and frequent system validations and evaluations. This work explores different data-reduction schemes and designs an approach that requires only a few CT scans. Three different kinds of approaches are included in this study: a conventional CHO/CSLO technique with a large sample size, a conventional CHO/CSLO technique with fewer samples, and an approach that we will show requires fewer samples to mimic conventional performance with a large sample size. The mean value and standard deviation of areas under ROC/EROC curve were estimated using the well-validated shuffle approach. The results indicate that an 80% data reduction can be achieved without loss of accuracy. This substantial data reduction is a step toward a practical tool for routine-task-based QA/QC CT system assessment. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)

Depuis la fin du 20ème siècle, l'imagerie médicale s'est fortement développée et représente aujourd'hui un moyen incontournable pour le diagnostic médical. Dans le domaine de la radiologie par rayons X, de nouveaux détecteurs numériques remplacent progressivement les anciennes techniques à film et permettent d'obtenir des images de meilleure qualité. Cette thèse, préparée en collaboration entre l'entreprise Trixell, constructeur de détecteurs plats numériques pour la radiographie, et le laboratoire Gipsa-Lab, s'inscrit dans le cadre général du contrôle qualité de ces détecteurs par analyse d'images. Les applications biomédicales mettant en jeu ces appareils, sont généralement particulièrement sensibles, et le principe de « zéro défaut » est de mise quant à la qualité des produits. Malgré les différents traitements, certains défauts peuvent être présents dans les images. Cette thèse est axée sur le développement de modèles de mesure de la visibilité des défauts, en cohérence avec l'observation d'un humain. Deux approches complémentaires sont développées : la première approche basée sur des expériences psychophysiques et la seconde approche de modélisation basée sur la théorie de décision. Par rapport aux modèles de visibilité existants, notre modèle prend en compte la perception humaine et notamment les saccades et fixations oculaires dans l'analyse des images : le test de visibilité est ainsi le produit de tests de visibilité locaux, calculés aux points saillants de l'image supposés indépendants. Les résultats montrent l'intérêt de notre approche, notamment pour des détecteurs statiques. En se fondant sur les résultats et une dernière expériences d'oculométrie, cette thèse suggère en perspective la prise en compte d'autres caractéristiques comme le nombre de fixations oculaires, et leur durée. / Since the beginning of the 20th century, medical imaging has significantly been improved and represents now an essential mean for medical diagnosis. In the field of radiology, new digital detectors are gradually replacing the old film techniques allowing a better image. This thesis, prepared in collaboration between the company Trixell, manufacturer of X-ray detectors, and the laboratory Gipsa-Lab, is part of the framework of quality control of these detectors by image analysis. Biomedical applications involved by these devices are particularly sensitive, and the principle of “zero artifact” is required to ensure the quality of the product. Despite the various processings, some artifacts may be present in the images.This thesis focuses on the development of models that quantify the visibility of artifacts in concordance to human observation. Two complementary approaches are developed : the first one is based on psychophysical experiments and the second one is a modeling approach based on decision theory. In comparison to existent models, our model takes into account perception characteristics including saccades and eye fixation in image analysis : the visibility test is thus the product of local visibility tests calculated on the salient points of the image and assumed to be independent. The results show the interest of our approach, especially for static detectors. Based on the results and a final eye-tracking experiment, this thesis suggests perspectives taking into account other characteristics such as the number of eye fixations and their duration.

BACKGROUND: Although the Image Quality (IQ) indices calculated by objective Model observers contains more favourable characteristics compared to Figure Of Merits (FOM) derived from the more common subjective evaluations of modern digital diagnostic fluoroscopy units, like CDRAD or the Leeds test-objects, practical issues in form of limited access to unprocessed raw data and intricate laboratory measurements have made the conventional computational methods too inefficient and laborious. One approach of the Statistical Decision Variables (CDV) analysis, made available in the FluoroQuality software, overcome these limitations by calculating the SNR2rate from information entirely based on image frames directly obtained from the imaging system, operating in its usual clinical mode.      AIM: The overall aim of the project has been to make the proposed Model observer methodology readily available and verified for use in common IQ tests that takes place in a hospital based on simple measuring procedures with the default image enhancement techniques turned on. This includes conversion of FluoroQuality to MATLAB, assessment of its applicability on a modern digital unit by means of comparisons of measured SNR2rate with the expected linear response predicted by the classical Rose model, assessment of the methods limiting and optimized imaging conditions (with regard to both equipment and software parameters) and dose-efficiency measurements of the SNR2rate/Doserate Dose-to-information (DI) index including both routine quality control of the detector and equipment parameter analyses.      MATERIALS AND METHODS: A Siemens Axiom Artis Zee MP diagnostic fluoroscopy unit, a Diamentor transmission ionisation chamber and a small T20 solid state detector have been used for acquisition of image data and measurements of Air Kerma-area product rate (KAP-rate) and Entrance Surface Air Kerma rate (ESAK-rate without backscatter). Two sets of separate non-attached test-details, of aluminium and tissue equivalent materials respectively, and a Leeds test object were used as contrasting signals. Dose-efficiency measurements consisted of variation of 4 different parameters: Source-Object-Distance, Phantom PMMA thickness, Field size and Dose rate setting. In addition to these, dimensions of the test details as well as computational parameters of the software, like ROI size and number of frames, were included in the theoretical analyses.      RESULTS: FluoroQuality has successfully been converted to MATLAB and the method has been verified with SNR2rate in accordance with the Rose model with only small deviations observed in contrast analyses, most likely reflecting the methods sensitivity in observing non-linear effects. Useful guidelines for measurement procedures with regard to accuracy and precision have been derived from the studies. Results from measurements of the (squared) DI-indices indicates comparable precision (≤ 8%) with the highest performing visual evaluations but with higher accuracy and reproducibility. What still remains for the method to compete with subjective routine QC tests is to integrate the SNR2rate measurements in an efficient enough QA program.