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Simon Wittl, M.Eng

Zentrum für angewandte Forschung

Technologie Campus Plattling CT

Wissenschaftlicher Mitarbeiter

ITC2 0.16

0991/3615-489

Sortierung:
Beitrag in Sammelwerk/Tagungsband
  • Gerald Fütterer
  • Michael Wagner
  • Lucas Bauer
  • Simon Wittl

Alignment and thermal drift aspects of a four-tilted-mirror student project telescope.

  • In:
  • Rolf Rascher
  • Christian Schopf

Bellingham, WA, USA pg. 111710L1-111710L9

DOI: 10.1117/12.2530076

(2019)

Beitrag in Sammelwerk/Tagungsband
  • Gerald Fütterer
  • Michael Wagner
  • Lucas Bauer
  • Simon Wittl

Four-Tilted-Mirror Telescope: Alignment and Stability Aspects.

  • In:
  • Technische Hochschule Deggendorf

Deggendorf pg. 153-158

(2019)

Beitrag in Sammelwerk/Tagungsband
  • Anton Weiss
  • Simon Wittl
  • Gabriel Herl
  • Simon Zabler

Simulated and experimental evaluation of the accuracy of twin robotic CT systems.

pg. 1-10

(2023)

Beitrag in Sammelwerk/Tagungsband
  • Simon Wittl
  • Anton Weiss
  • Gabriel Herl
  • Simon Zabler

Keep Attention to the Mapping: Application of AI for Geometric X-Ray RoboCT Scan Calibration.

pg. 1-7

(2023)

Zeitschriftenartikel
  • F. Sukowski
  • Daniel Rauch
  • R. Schielein
  • T. Schön
  • A. Waldyra
  • M. Fries
  • A. Maier
  • L.-S. Schneider
  • Gabriel Herl
  • Simon Wittl
  • Simon Zabler
  • et al.

SmartCT - Development of AI based methods for automation of RoboCT scan procedures.

In: e-Journal of Nondestructive Testing (eJNT) (13th Conference on Industrial Computed Tomography (iCT) 2024, 6-9 Feb 2024; School of Engineering, Wals Campus, Austria) (vol. 29)

(2024)

DOI: 10.58286/29232

Abstract anzeigen

The SmartCT system consists of AI based methods that assist users of robot-based CT systems (RoboCT) to digitalize industrial parts of almost arbitrary size and geometrical complexity with a high degree of automation. Due to the high number of degrees of freedom and thus complexity, RoboCT scan procedures are difficult to parametrize with respect to collision safety and image quality. The SmartCT assist functions help users to perform measurements quickly and safely while using advanced algorithms for geometrical image correction and 3D-CT volume reconstruction.
Zeitschriftenartikel
  • Simon Wittl
  • Anton Weiss
  • Gabriel Herl
  • Simon Zabler
  • P. Dewailly
  • R. Le Goff

Unveiling the Full Picture: Advanced Scanning Procedure for Complete Large Component Scans via Twin Robotic Computed Tomography.

In: e-Journal of Nondestructive Testing (eJNT) (13th Conference on Industrial Computed Tomography (iCT) 2024, 6-9 Feb 2024; School of Engineering, Wals Campus, Austria) (vol. 29)

(2024)

DOI: 10.58286/29260

Abstract anzeigen

Twin robotic computed tomography (RoboCT) offers a high degree of flexibility. RoboCT systems are commonly used for either flexible 2D inspection of large areas or 3D inspection of small areas in large objects. This study introduces a workflow to perform a full CT scan of large objects that exceed the field of view with the help of RoboCT. To achieve this, we virtually enlarges the detector's size to enable reconstruction of larger objects or large region of interests and use projection stitching with a multi-angle Xray projection registration method.
Zeitschriftenartikel
  • Daniel Rauch
  • Simon Wittl
  • Simon Zabler

rosct: A distributed, scriptable CT control framework for iterative research-oriented method and application development.

In: e-Journal of Nondestructive Testing (eJNT) (13th Conference on Industrial Computed Tomography (iCT) 2024, 6-9 Feb 2024; School of Engineering, Wals Campus, Austria) (vol. 29)

(2024)

DOI: 10.58286/29247

Abstract anzeigen

Industrial Computed Tomography (CT) scan control software must meet the highest standards of reliability, performance, and efficiency, which is why these criteria also form the main focus in their system design. Current systems excel when utilized for the specific task and workflow for which they were originally designed by the manufacturer. However, during early development of new CT scanners, research-oriented method development and during implementation of custom inspection tasks, different requirements can be observed. Due to the iterative, dynamic approach in these areas, the control software must also be flexible, adaptable, and easily automatable while still being user friendly. To reduce iteration times further, the native integration of common research-oriented development toolsets and 3rd party ecosystem are key. In addition, CT as technology is evolving in regards of actorics (e.g., twin robotic CT systems) and model driven design (e.g., digital twins), all not fully supported by most current control platforms, which hinders development speed and adaptation. To summarize, there is a noticeable gap between the requirements of researchers and development departments regarding the capabilities of the existing CT systems. This discrepancy motivates the need to explore and develop CT control systems that are open, easily adaptable, and extendable. These insights are put into practice with the novel rosct CT control framework, which is presented in this paper.
Zeitschriftenartikel
  • D. Rückert
  • L. Butzhammer
  • Simon Wittl
  • Gabriel Herl
  • T. Hausotte
  • P. Kurth

Uncalibrated CT Reconstruction for One-Shot Scanning of Arbitrary Trajectories.

In: e-Journal of Nondestructive Testing (eJNT) (13th Conference on Industrial Computed Tomography (iCT) 2024, 6-9 Feb 2024; School of Engineering, Wals Campus, Austria) (vol. 29)

(2024)

DOI: 10.58286/29231

Abstract anzeigen

CT systems with high degrees of freedom such as robot-guided setups allow CT scanning with arbitrary 3D trajectories. However, many existing systems require an additional calibration scan to determine the exact source/detector poses of new trajectories. In this paper, we show that using a novel reconstruction technique, the calibration scan can be omitted with only a minor loss in accuracy. This is demonstrated on experimental CT scans using two different CT systems that allow for non-standard 3D scan trajectories, a twin-robotic system and an industrial cone beam scanner equipped with a hexapod manipulator. Additionally, the applicability of the self-calibrating reconstruction technique for motion compensation is shown. The presented method simplifies robotic and non-standard CT scanning, doubles its throughput, and allows precise CT reconstruction for systems with geometric misalignments.
Vortrag
  • Simon Wittl

Real Data Validation of RoboCT Trajectory Optimization: Ensuring Quality in CT Imaging.

Plattling 10.07.2024.

(2024)

Zeitschriftenartikel
  • L. Butzhammer
  • Niklas Handke
  • Simon Wittl
  • Gabriel Herl
  • T. Hausotte

Direct assessment of the influence of pose repeatability on the accuracy of dimensional measurements for computed tomography systems with high degrees of freedom.

In: Measurement Science and Technology (vol. 36) , pg. 025401

(2025)

DOI: 10.1088/1361-6501/ada05a

Abstract anzeigen

Industrial x-ray computed tomography (CT) systems with high geometric flexibility are increasingly utilized for large-scale measurement objects or challenging measurement tasks. To maintain high accuracy when deviating from the established circular scan trajectory, trajectory calibration methods using multi-sphere reference objects with known marker positions are commonly employed. These multi-sphere objects can either be scanned together with the measurement object (online trajectory calibration) or in a separate scan (offline trajectory calibration). While offline calibration increases machine time, it generally results in higher scan quality. However, a sufficient pose repeatability is necessary to ensure comparable or even superior accuracy to online calibration. In this contribution, we present a straightforward procedure to compare both types of trajectory calibration in a way that the differences of the results can directly be traced back to the influence of the pose repeatability. The multi-sphere reference object is not only used for trajectory calibration, but simultaneously as a measurement object for repeated measurements. The methodology is tested on both a twin robotic CT system and a conventional CT system that is additionally equipped with a hexapod manipulator for adaptive object tilting. Results showed, independent from the type of trajectory calibration, systematic measurement errors in the order of 10−5–10−4 of measured sphere distances and sphericity values below 50 μ. For sphere distances, random errors were increased by a factor of 5 due to the offline trajectory calibration, but were still low (μ) in comparison to systematic errors and the spread of different measurement features. Overall, both investigated systems demonstrated sufficient positioning repeatability for offline trajectory calibration. The method is in general also applicable to any other types of manipulator systems used for CT devices. It provides a workflow for the decision which type of trajectory calibration is preferable for a given CT system.
Zeitschriftenartikel
  • Anton Weiss
  • Simon Wittl
  • Gabriel Herl
  • Simon Zabler
  • M. Sause

Decreasing the acquisition time for cost-effective CT imaging with industrial robots: A FlyBy approach.

In: e-Journal of Nondestructive Testing (eJNT) (8th Pan American Conference for Nondestructive Testing 2025) (vol. 30)

(2025)

DOI: 10.58286/31365

Abstract anzeigen

Conventional industrial X-Ray CT systems are limited in their movement because of their limited degrees of freedom and overall design. Equipping CT with two industrial robotic arms, e.g. for manipulating source and detector, overcomes this limitation. Industrial robots are less restricted in the positioning and orientation of their X-ray tools than comparable industrial CT systems, making them flexible manipulators. However, their absolute positioning accuracy is usually below the minimum requirement for use in computed tomography. This paper proposes a calibration method with a variable, low-cost calibration body that allows pose correction of arbitrary projection geometries. The results from a twin robotic CT system will be evaluated via simulated projection data and actual experimental computer tomographic reconstruction.
Zeitschriftenartikel
  • Anton Weiss
  • Simon Wittl
  • Gabriel Herl
  • Simon Zabler
  • A. Trauth
  • M. Sause

Safeguarding accuracy for CT imaging with industrial robots: Efficient calibration methods for arbitrary trajectories.

In: e-Journal of Nondestructive Testing (eJNT) (14th Conference on Industrial Computed Tomography (iCT), 4-7 February 2025; Antwerp, Belgium (iCT 2025)) (vol. 30)

(2025)

DOI: 10.58286/30725

Abstract anzeigen

Conventional industrial computed tomography (CT) systems are constrained in their choice of acquisition trajectories due to their mechanical design. These systems are very precise instruments since they do only move on primarily highly accurate rotational stages. In order to be able to scan an arbitrary Region of Interest (ROI), regardless of the position, size and weight of the specimen, conventional industrial robots can be used as flexible 6 degrees of freedom (DOF) manipulators. For example in a twin robot computed tomography system, acquisition geometries with arbitrary tool poses can be realized. In scientific applications, the quality of the CT volume image is of primary interest, whereas in an industrial environment it is often a matter of balancing quality and acquisition time. Common industrial robots cannot achieve the required positional accuracy without calibration to generate an ideal reconstruction. In the presented study, methods for the geometric correction of CT scans are compared. Image based correction is compared to general machine calibration and full pose tracking by laser trackers. Image quality metrics such as the Modulation Transfer Function, Shannon entropy and Tenengrad variance are utilized to evaluate and compare the reconstruction quality of the various correction and calibration approaches. The assessment of the reconstruction quality revealed a comparable reconstruction quality between the approaches, with the machine calibration approach emerging as one of the best, while also reducing the time-intensive correction overhead.
Zeitschriftenartikel
  • Gabriel Herl
  • Simon Wittl
  • Alexander Jung
  • Niklas Handke
  • Anton Weiss
  • M. Eberhorn
  • S. Oeckl
  • Simon Zabler

RoboCT: The State and Current Challenges of Industrial Twin Robotic CT Systems.

In: Sensors (vol. 25)

(2025)

DOI: 10.3390/s25103076

Abstract anzeigen

Twin robotic X-ray computed tomography (CT) refers to CT systems in which two robotic arms are used to independently move the X-ray source and the X-ray detector around the object. This setup enables flexible CT scans by using robots to move the X-ray source and the X-ray detector around an object's region of interest. This allows scans of large objects, image quality optimization and scan time reduction. Despite these advantages, robotic CT systems still face challenges that limit their widespread adoption. This paper discusses the state of twin robotic CT and its current main challenges. These challenges include the optimization of scanning trajectories, precise geometric calibration and advanced 3D reconstruction techniques.
Zeitschriftenartikel
  • Simon Zabler
  • A. Klos
  • P. Lhuissier
  • L. Salvo
  • M. Farahmandi
  • Simon Wittl

Denoising and deconvolving CT images of unknown origin: comparing linear Wiener-deconvolution with deep convolutional neural network Noise2Inverse.

In: e-Journal of Nondestructive Testing (eJNT) (14th Conference on Industrial Computed Tomography (iCT), 4-7 February 2025; Antwerp, Belgium (iCT 2025)) (vol. 30)

(2025)

DOI: 10.58286/30718

Abstract anzeigen

Low-dose CT scans are very fast, but they feature strong pixel noise which, in turn, invites for efficient denoising the same way that strong image blur invites for sharpening the images. Wiener-deconvolution serves as a starting point, combining these two operations in a linear Fourier filter. It may apply in 2D or 3D and requires merely estimates of the Signal-to-Noise Ratio SNR2 as well as the system Modulation Transfer Function (MTF). Meanwhile, any linear filter is unable to adapt to local contrast variations in the images. Therefore, convolutional neural networks (CNN) such as MSDnet or UNet can significantly improve reconstructions from low-dose CT scans thanks to their non-linear nature. The Noise2Inverse framework allows for training these CNN using a split-and-merge of two subsets generated from one raw CT dataset. This study investigates denoising by N2I with respect to the input data quality, the CNN network architecture and the fidelity of the features in the resulting denoised volume images. Unlike Wiener filtering, N2I is far more effective in removing pixel noise. Yet, these models give the vague impression that they might generate ghosts of small features (pores or spots) in the object. Image quality metrics like Fourier Shell Correlation and SNR2 power spectra show clear improvement. In particular, Noise2Inverse preserves the signal power spectrum of all scans reliably. Nevertheless, locally inspecting image features must remain a core technique when the CNN models are applied, i.e. for industrial inspection.