Research Presentation Session

RPS 113 - The ultimate goal: improvement of image quality

Lectures

1
RPS 113 - Bin-combination-based noise reduction for metal artifact reduction in photon-counting CT

RPS 113 - Bin-combination-based noise reduction for metal artifact reduction in photon-counting CT

05:04P. Trapp, Heidelberg / DE

2
RPS 113 - Model observer assessment of photon-counting-detector coronary CT angiography and comparison with energy-integrating-detector CT

RPS 113 - Model observer assessment of photon-counting-detector coronary CT angiography and comparison with energy-integrating-detector CT

09:17D. Rotzinger, Lausanne / CH

3
RPS 113 - Virtual monoenergetic images from dual-energy CT: systematic assessment of task-based image quality performance for dual-source dual-energy CT

RPS 113 - Virtual monoenergetic images from dual-energy CT: systematic assessment of task-based image quality performance for dual-source dual-energy CT

04:51A. Euler, Zurich / CH

4
RPS 113 - Integrated investigation of radiomic features reproducibility in NSCLC patients: the impact of scanner, x-ray tube voltage and strength of reconstruction algorithms in contrast-enhanced CT images

RPS 113 - Integrated investigation of radiomic features reproducibility in NSCLC patients: the impact of scanner, x-ray tube voltage and strength of reconstruction algorithms in contrast-enhanced CT images

04:54L. Rinaldi, Milan / IT

5
RPS 113 - Image quality characterisation of a biplane angiographic equipment with moving details and generalised spatio-temporal model observers

RPS 113 - Image quality characterisation of a biplane angiographic equipment with moving details and generalised spatio-temporal model observers

04:47R. Villa, Monza / IT

6
RPS 113 - Effect on image quality and dose reduction of a new deep learning reconstruction algorithm for CT compared with a hybrid and an advanced MBIR algorithms: a phantom study

RPS 113 - Effect on image quality and dose reduction of a new deep learning reconstruction algorithm for CT compared with a hybrid and an advanced MBIR algorithms: a phantom study

05:02J. Greffier, Nimes / FR

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