Dr. Steffen Kappler Profile

Dr. Steffen Kappler

Director XP Technology & Innovation at Siemens Healthineers

SPIE Involvement:

Author

Publications (55)

Proceedings Article | 1 April 2024 Presentation + Paper

Hybrid thick-slice reconstruction in wide-angle DBT for optimal micro-calcification and mass perceptibility

Marcel Beister, Ferdinand Lueck, Ludwig Ritschl, Steffen Kappler

Proceedings Volume 12925, 129250O (2024) https://doi.org/10.1117/12.3006969

KEYWORDS: Digital breast tomosynthesis, Visibility, Reconstruction algorithms, Diagnostics, Tunable filters, Data acquisition, Voxels, Tissues, Blood vessels, Anatomy

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Proceedings Article | 1 April 2024 Poster + Paper

Investigation of correction and decomposition algorithms in bedside x-ray imaging simulating a multi-layer flat panel detector

Jamin Schaefer, Stephen Liu, Steffen Kappler, Ferdinand Lueck, Ludwig Ritschl, Thomas Weber, Wojciech Zbijewski, Georg Rose

Proceedings Volume 12925, 1292536 (2024) https://doi.org/10.1117/12.3006758

KEYWORDS: Bone, Monte Carlo methods, Adipose tissue, Sensors, Detection and tracking algorithms, Computer simulations, Attenuation, X-ray imaging, Computed tomography, X-rays

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Proceedings Article | 1 April 2024 Poster + Paper

Noise gate: a physics-driven control method for deep learning denoising in x-ray imaging

Magdalena Herbst, Marcel Beister, Stephan Dwars, Dominik Eckert, Ludwig Ritschl, Christopher Syben, Steffen Kappler

Proceedings Volume 12925, 129253X (2024) https://doi.org/10.1117/12.3006446

KEYWORDS: Denoising, X-ray imaging, Deep learning, X-rays, Tunable filters

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Proceedings Article | 1 April 2024 Presentation + Paper

Breast shape-specific subtraction for improved contrast enhanced mammography imaging

M. Pinto, K. Michielsen, R. Biniazan, S. Kappler, I. Sechopoulos

Proceedings Volume 12925, 129250Q (2024) https://doi.org/10.1117/12.3006717

KEYWORDS: Breast, Image segmentation, Mammography, X-rays, Monte Carlo methods, Image processing, Computer simulations

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Contrast-enhanced mammography (CEM) offers a promising alternative to address the limitations of digital mammography, particularly in cases of dense breast tissue, which compromises the performance of non-contrast x-ray imaging modalities. CEM uses iodinated contrast material to enhance cancer detection in denser breasts and provides critical functional information about suspicious findings. However, the process of combining images acquired with different x-ray energy spectra in CEM can introduce artifacts, challenging interpretation and confidence in CEM images. This study presents novel approaches to improve CEM image quality. First, deep learning (DL)-based algorithms for scatter correction in both low-energy and high-energy images are proposed to enhance contrast-enhancement patterns and iodine quantification. Additionally, a unique deep learning network is introduced to predict pixel-by-pixel the compressed breast thickness, enabling the use of local thickness-based image subtraction-weighting maps throughout the breast area. Results in phantom cases demonstrate the effectiveness of the scatter correction models in predicting the scatter signal, even in cases with the anti-scatter grid present. The thickness map model accurately estimates the local thickness, particularly in the constant thickness area of the breast. Comparison with clinical data revealed good agreement between estimated thickness maps and ground truth, with minor discrepancies attributed to alignment issues. Furthermore, the study explored the combined use of scatter correction and thickness-based weighting maps in creating recombined CEM images. This approach showed a marginal positive impact due to scatter correction, with larger improvements observed in the signal intensity homogeneity at the border of the breast. These advancements aim to enhance the CEM diagnostic accuracy, making it a valuable tool for breast cancer detection and evaluation, especially in cases with dense breast tissue.

SPIE Journal Paper | 7 December 2023

Deep learning based tomosynthesis denoising: a bias investigation across different breast types

Dominik Eckert, Julia Wicklein, Magdalena Herbst, Stephan Dwars, Ludwig Ritschl, Steffen Kappler, Sebastian Stober

JMI, Vol. 10, Issue 06, 064003, (December 2023) https://doi.org/10.1117/12.10.1117/1.JMI.10.6.064003

KEYWORDS: Denoising, Breast, Education and training, Digital breast tomosynthesis, Tomosynthesis, Computer simulations, Deep learning, X-rays, Breast density, Photons

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Proceedings Article | 7 April 2023 Poster + Paper

First evaluation of 3D measurements of the compressed breast shape for digital breast tomosynthesis in the medio-lateral oblique view

M. Pinto, T. Egten, K. Michielsen, R. Biniazan, S. Kappler, I. Sechopoulos

Proceedings Volume 12463, 124632M (2023) https://doi.org/10.1117/12.2653842

KEYWORDS: Breast, Digital breast tomosynthesis, 3D modeling, Systems modeling, 3D scanning, 3D acquisition, Image compression, Data modeling, Scanners, Optical scanning systems

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Proceedings Article | 18 October 2022 Open Access

Dual-energy cone-beam CT with three-material decomposition for bone marrow edema imaging

Stephen Liu, Magdalena Herbst, Thomas Weber, Sebastian Vogt, Ludwig Ritschl, Steffen Kappler, Jeffrey Siewerdsen, Wojciech Zbijewski

Proceedings Volume 12304, 123040Z (2022) https://doi.org/10.1117/12.2646391

KEYWORDS: Medical image reconstruction, Bone, X-ray computed tomography, Sensors, X-rays, Medical imaging, Aluminum, Physics, Photons, Signal attenuation, Monte Carlo methods

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Proceedings Article | 13 July 2022 Paper

Optimized signal of calcifications in wide-angle digital breast tomosynthesis systems: a virtual clinical study

Liesbeth Vancoillie, Lesley Cockmartin, Ferdinand Lueck, Nicholas Marshall, Ralf Nanke, Steffen Kappler, Hilde Bosmans

Proceedings Volume 12286, 1228604 (2022) https://doi.org/10.1117/12.2625772

KEYWORDS: Digital breast tomosynthesis, Breast, Reconstruction algorithms, Computer simulations, Clinical trials, X-rays, Visibility, Virtual reality

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PURPOSE: To investigate differences in microcalcification detection performance for different acquisition setups in digital breast tomosynthesis (DBT), a convex dose distribution and sparser number of projections compared to the standard set-up was evaluated via a virtual clinical trial (VCT). METHODS AND MATERIALS: Following the Institutional Review Board (IRB) approval and patient consent, mediolateral oblique (MLO) DBT views were acquired at twice the automatic exposure controlled (AEC) dose level; omitting the craniocaudal (CC) view limited the total examination dose. Microcalcification clusters were simulated into the DBT projections and noise was added to simulate lower dose levels. Three set-ups were evaluated: (1) 25 DBT projections acquired with a fixed dose/projection at the clinically used AEC dose level, (2) 25 DBT projections with dose/projection following a convex dose distribution along the scan arc, and (3) 13 DBT projections at higher dose with the total scan dose equal to the AEC dose level and preserving the angular range of 50° (sparse). For the convex set-up, dose/projection started at 0.035 mGy at the extremes and increased to 0.163 mGy for the central projection. A Siemens prototype algorithm was used for reconstruction. An alternative free-response receiver operating characteristic (AFROC) study was conducted with 6 readers to compare the microcalcification detection between the acquisition set-ups. Sixty cropped VOIs of 50x50x(breast thickness) mm3 per set-up were included, of which 50% contained a microcalcification cluster. In addition to localization of the cluster, the readers were asked to count the individual calcifications. The area under the AFROC curve was used to compare the different acquisition set-ups and a paired t-test was used to test significance. RESULTS: The AUCs for the standard, convex and sparse set-up were 0.97±0.01, 0.95±0.02 and 0.89±0.03, respectively, indicating no significant difference between standard and convex set-up (p=0.309), but a significant decrease in detectability was found for the sparse set-up (p=0.001). The number of detected calcifications per cluster was not significantly different between standard and convex set-ups (p=0.049), with 42%±9% and 40%±8%, respectively. The sparse set-up scored lower with a relative number of detected microcalcifications of 34%±11%, but this decrease was not significant (p=0.031). CONCLUSION: A convex dose distribution that increased dose along the scan arc towards the central projections did not increase detectability of microcalcifications in the DBT planes compared to the current AEC set-up. Conversely, a sparse set of projections acquired over the total scan arc decreased microcalcification detectability compared to the variable dose and current clinical set-up.

Proceedings Article | 4 April 2022 Presentation + Paper

Feasibility of dual-energy cone-beam CT of bone marrow edema using dual-layer flat panel detectors

Stephen Liu, Chumin Zhao, Magdalena Herbst, Thomas Weber, Sebastian Vogt, Ludwig Ritschl, Steffen Kappler, Jeffrey Siewerdsen, Wojciech Zbijewski

Proceedings Volume 12031, 120311J (2022) https://doi.org/10.1117/12.2613211

KEYWORDS: Bone, Collimation, Sensors, Copper, X-ray computed tomography, Medical imaging, Error analysis, Spectral calibration, Physics, Monte Carlo methods

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Purpose: We investigated the feasibility of detection and quantification of bone marrow edema (BME) using dual-energy (DE) Cone-Beam CT (CBCT) with a dual-layer flat panel detector (FPD) and three-material decomposition. Methods: A realistic CBCT system simulator was applied to study the impact of detector quantization, scatter, and spectral calibration errors on the accuracy of fat-water-bone decompositions of dual-layer projections. The CBCT system featured 975 mm source-axis distance, 1,362 mm source-detector distance and a 430 × 430 mm² dual-layer FPD (top layer: 0.20 mm CsI:Tl, bottom layer: 0.55 mm CsI:Tl; a 1 mm Cu filter between the layers to improve spectral separation). Tube settings were 120 kV (+2 mm Al, +0.2 mm Cu) and 10 mAs per exposure. The digital phantom consisted of a 160 mm water cylinder with inserts containing mixtures of water (volume fraction ranging 0.18 to 0.46) - fat (0.5 to 0.7) - Ca (0.04 to 0.12); decreasing fractions of fat indicated increasing degrees of BME. A two-stage three-material DE decomposition was applied to DE CBCT projections: first, projection-domain decomposition (PDD) into fat-aluminum basis, followed by CBCT reconstruction of intermediate base images, followed by image-domain change of basis into fat, water and bone. Sensitivity to scatter was evaluated by i) adjusting source collimation (12 to 400 mm width) and ii) subtracting various fractions of the true scatter from the projections at 400 mm collimation. The impact of spectral calibration was studied by shifting the effective beam energy (± 2 keV) when creating the PDD lookup table. We further simulated a realistic BME imaging framework, where the scatter was estimated using a fast Monte Carlo (MC) simulation from a preliminary decomposition of the object; the object was a realistic wrist phantom with an 0.85 mL BME stimulus in the radius. Results: The decomposition is sensitive to scatter: approx. <20 mm collimation width or <10% error of scatter correction in a full field-of-view setting is needed to resolve BME. A mismatch in PDD decomposition calibration of ± 1 keV results in ~25% error in fat fraction estimates. In the wrist phantom study with MC scatter corrections, we were able to achieve ~0.79 mL true positive and ~0.06 mL false positive BME detection (compared to 0.85 mL true BME volume). Conclusions: Detection of BME using DE CBCT with dual-layer FPD is feasible, but requires scatter mitigation, accurate scatter estimation, and robust spectral calibration.

Proceedings Article | 4 April 2022 Presentation + Paper

Deep learning scatter estimation for breast tomosynthesis based on a realistic compressed breast shape model in the CC view

M. Pinto, K. Michielsen, A. Rodríguez-Ruiz, R. Biniazan, S. Kappler, I. Sechopoulos

Proceedings Volume 12031, 120310C (2022) https://doi.org/10.1117/12.2610772

KEYWORDS: Breast, Monte Carlo methods, Digital breast tomosynthesis, Image segmentation, X-rays, Data modeling, Neural networks

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Proceedings Article | 4 April 2022 Poster + Paper

Deep learning based denoising of mammographic x-ray images: an investigation of loss functions and their detail-preserving properties

Dominik Eckert, Ludwig Ritschl, Magdalena Herbst, Julia Wicklein, Sulaiman Vesal, Steffen Kappler, Andreas Maier, Sebastian Stober

Proceedings Volume 12031, 120311T (2022) https://doi.org/10.1117/12.2612403

KEYWORDS: Denoising, X-rays, Digital breast tomosynthesis, X-ray imaging, Photons, Mammography, Sensors, Physics, Signal to noise ratio, Interference (communication)

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Proceedings Article | 15 February 2021 Presentation + Paper

Image-domain cardiac motion compensation in multidirectional digital chest tomosynthesis

Chumin Zhao, Magdalena Herbst, Thomas Weber, Sebastian Vogt, Ludwig Ritschl, Steffen Kappler, Jeffrey Siewerdsen, Wojciech Zbijewski

Proceedings Volume 11595, 1159525 (2021) https://doi.org/10.1117/12.2581287

KEYWORDS: Chest, Heart, X-rays, X-ray detectors, Sensors, X-ray computed tomography, Visualization, Robotics, Robotic systems

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Clinical study for evaluation of an inflatable air cushion to reduce patient discomfort during tomosynthesis compression

Madeleine Hertel, Michael Golatta, Steffen Kappler, Ralf Nanke, Marija Juskic, Ramon Smith, Benedikt Schaefgen, Georg Rose, Marcus Radicke

Proceedings Volume 11595, 115954U (2021) https://doi.org/10.1117/12.2580711

KEYWORDS: Breast, Image quality, Image compression, Tissues, Prototyping, Mammography, Image quality standards, Breast imaging, Analytical research

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Proceedings Article | 15 February 2021 Presentation + Paper

Effects of x-ray scatter in quantitative dual-energy imaging using dual-layer flat panel detectors

Chumin Zhao, Stephen Liu, Wenying Wang, Magdalena Herbst, Thomas Weber, Sebastian Vogt, Ludwig Ritschl, Steffen Kappler, J. Webster Stayman, Jeffrey Siewerdsen, Wojciech Zbijewski

Proceedings Volume 11595, 115952A (2021) https://doi.org/10.1117/12.2581822

KEYWORDS: Sensors, X-rays, X-ray imaging, X-ray detectors, Dual energy imaging, Error analysis, Scintillators, Minerals, Copper, Cesium

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Purpose: We compare the effects of scatter on the accuracy of areal bone mineral density (BMD) measurements obtained using two flat-panel detector (FPD) dual-energy (DE) imaging configurations: a dual-kV acquisition and a dual-layer detector. Methods: Simulations of DE projection imaging were performed with realistic models of x-ray spectra, scatter, and detector response for dual-kV and dual-layer configurations. A digital body phantom with 4 cm Ca inserts in place of vertebrae (concentrations 50 - 400 mg/mL) was used. The dual-kV configuration involved an 80 kV low-energy (LE) and a 120 kV high-energy (HE) beam and a single-layer, 43x43 cm FPD with a 650 μm cesium iodide (CsI) scintillator. The dual-layer configuration involved a 120 kV beam and an FPD consisting of a 200 μm CsI layer (LE data), followed by a 1 mm Cu filter, and a 550 μm CsI layer (HE data). We investigated the effects of an anti-scatter grid (13:1 ratio) and scatter correction. For the correction, the sensitivity to scatter estimation error (varied ±10% of true scatter distribution) was evaluated. Areal BMD was estimated from projection-domain DE decomposition. Results: In the gridless dual-kV setup, the scatter-to-primary ratio (SPR) was similar for the LE and HE projections, whereas in the gridless dual layer setup, the SPR was ~26% higher in the LE channel (top CsI layer) than in the HE channel (bottom layer). Because of the resulting bias in LE measurements, the conventional projection-domain DE decomposition could not be directly applied to dual-layer data; this challenge persisted even in the presence of a grid. In contrast, DE decomposition of dual-kV data was possible both without and with the grid; the BMD error of the 400 mg/mL insert was -0.4 g/cm² without the grid and +0.3 g/cm² with the grid. The dual-layer FPD configuration required accurate scatter correction for DE decomposition: a -5% scatter estimation error resulted in -0.1 g/cm² BMD error for the 50 mg/mL insert and a -0.5 g/cm² BMD error for the 400 mg/mL with a grid, compared to <0.1 g/cm² for all inserts in a dual-kV setup with the same scatter estimation error. Conclusion: This comparative study of quantitative performance of dual-layer and dual-kV FPD-based DE imaging indicates the need for accurate scatter correction in the dual-layer setup due to increased susceptibility to scatter errors in the LE channel.

Proceedings Article | 16 March 2020 Presentation + Paper

Slot-scan dual-energy measurement of bone mineral density on a robotic x-ray system

C. Zhao, C. Luckner, M. Herbst, S. Vogt, L. Ritschl, S. Kappler, J. Siewerdsen, W. Zbijewski

Proceedings Volume 11312, 1131205 (2020) https://doi.org/10.1117/12.2549631

KEYWORDS: Bone, X-rays, Dual energy x-ray absorptiometry, Spine, Minerals, Robotics, Robotic systems, Radiography, Sensors, X-ray imaging

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Purpose: We investigate the feasibility of slot-scan dual-energy x-ray absorptiometry (DXA) on robotic x-ray platforms capable of synchronized source and detector translation. This novel approach will enhance the capabilities of such platforms to include quantitative assessment of bone quality using areal bone mineral density (aBMD), normally obtained only with a dedicated DXA scanner. Methods: We performed simulation studies of a robotized x-ray platform that enables fast linear translation of the x-ray source and flat-panel detector (FPD) to execute slot-scan dual-energy (DE) imaging of the entire spine. Two consecutive translations are performed to acquire the low-energy (LE, 80 kVp) and high-energy (HE, 120 kVp) data in <15 sec total time. The slot views are corrected with convolution-based scatter estimation and backprojected to yield tiled long-length LE and HE radiographs. Projection-based DE decomposition is applied to the tiled radiographs to yield (i) aBMD measurements in bone, and (ii) adipose content measurement in bone-free regions. The feasibility of achieving accurate aBMD estimates was assessed using a high-fidelity simulation framework with a digital body phantom and a realistic bone model covering a clinically relevant range of mineral densities. Experiments examined the effects of slot size (1 – 20 cm), scatter correction, and patient size/adipose content (waist circumference: 77 – 95 cm) on the accuracy and reproducibility of aBMD. Results: The proposed combination of backprojection-based tiling of the slot views and DE decomposition yielded bone density maps of the spine that were free of any apparent distortions. The x-ray scatter increased with slot width, leading to aBMD errors ranging from 0.2 g/cm² for a 5 cm slot to 0.7 g/cm² for a 20 cm slot when no scatter correction was applied. The convolution-based correction reduced the aBMD error to within 0.02 g/cm² for slot widths <10 cm. Reproducible aBMD measurements across a range of body sizes (aBMD variability <0.1 g/cm²) were achieved by applying a calibration based on DE adipose thickness estimates from peripheral body sites. Conclusion: The feasibility of accurate and reproducible aBMD measurements on an FPD-based x-ray platform was demonstrated using DE slot scan trajectories, backprojection-domain decomposition, scatter correction, and adipose precorrection.

Proceedings Article | 28 May 2019 Paper

Optimization of cone-beam CT scan orbits for cervical spine imaging

Chumin Zhao, Magdalena Herbst, Sebastian Vogt, Ludwig Ritschl, Steffen Kappler, Jeffrey Siewerdsen, Wojciech Zbijewski

Proceedings Volume 11072, 110720U (2019) https://doi.org/10.1117/12.2534754

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Purpose: We investigate cone-beam CT (CBCT) imaging protocols and scan orbits for 3D cervical spine imaging on a twin-robotic x-ray imaging system (Multitom Rax). Tilted circular scan orbits are studied to assess potential benefits in visualization of lower cervical vertebrae, in particular in low-dose imaging scenarios. Methods: The Multitom Rax system enables flexible scan orbit design by using two robotic arms to independently move the x-ray source and detector. We investigated horizontal and tilted circular scan orbits (up to 45° tilt) for 3D imaging of the cervical spine. The studies were performed using an advanced CBCT simulation framework involving GPU accelerated x-ray scatter estimation and accurate modeling of x-ray source, detector and noise. For each orbit, the x-ray scatter and scatter-to-primary ratio (SPR) were evaluated; cervical spine image quality was characterized by analyzing the contrast-to-noise ratio (CNR) for each vertebrae. Performance evaluation was performed for a range of scan exposures (263 mAs/scan – 2.63 mAs/scan) and standard and dedicated low dose reconstruction protocols. Results: The tilted orbit reduces scatter and increases primary detector signal for lower cervical vertebrae because it avoids ray paths crossing through both shoulders. Orbit tilt angle of 35° was found to achieve a balanced performance in visualization of upper and lower cervical spine. Compared with a flat orbit, using the optimized 35° tilted orbit reduces lateral projection SPR at the C7 vertebra by <40%, and increases CNR by 220% for C6 and 76% for C7. Adequate visualization of the vertebrae with CNR <1 was achieved for scan exposures as low as 13.2 mAs / scan, corresponding to ~3 mGy absorbed spine dose. Conclusion: Optimized tilted scan orbits are advantageous for CBCT imaging of the cervical spine. The simulation studies presented here indicate that CBCT image quality sufficient for evaluation of spine alignment and intervertebral joint spaces might be achievable at spine doses below 5 mGy.

Proceedings Article | 4 March 2019 Presentation + Paper

Mammographic breast density classification using a deep neural network: assessment based on inter-observer variability

N. Kaiser, A. Fieselmann, S. Vesal, N. Ravikumar, L. Ritschl, S. Kappler, A. Maier

Proceedings Volume 10952, 109520O (2019) https://doi.org/10.1117/12.2513420

KEYWORDS: Breast, Neural networks, Breast cancer, Convolutional neural networks, Image segmentation, Tissues, Image classification, Feature extraction, Mammography, Algorithm development

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Proceedings Article | 1 March 2019 Presentation + Paper

A robotic x-ray cone-beam CT system: trajectory optimization for 3D imaging of the weight-bearing spine

C. Zhao, M. Herbst, S. Vogt, L. Ritschl, S. Kappler, J. Siewerdsen, W. Zbijewski

Proceedings Volume 10948, 109481L (2019) https://doi.org/10.1117/12.2513433

KEYWORDS: X-rays, Sensors, Spine, Monte Carlo methods, X-ray imaging, Imaging systems, Robotics, Stereoscopy, X-ray computed tomography, Robotic systems

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Purpose: We optimize scan orbits and acquisition protocols for 3D imaging of the weight-bearing spine on a twin-robotic x-ray system (Multitom Rax). An advanced Cone-Beam CT (CBCT) simulation framework is used for systematic optimization and evaluation of protocols in terms of scatter, noise, imaging dose, and task-based performance in 3D image reconstructions. Methods: The x-ray system uses two robotic arms to move an x-ray source and a 43×43 cm² flat-panel detector around an upright patient. We investigate two classes of candidate scan orbits, both with the same source-axis distance of 690 mm: circular scans with variable axis-detector distance (ADD, air gap) ranging from 400 to 800 mm, and elliptical scans, where the ADD smoothly changes between the anterior-posterior view (ADDAP) and the lateral view (ADDLAT). The study involved elliptical orbits with fixed ADDAP of 400 mm and variable ADDLAT, ranging 400 to 800 mm. Scans of human lumbar spine were simulated using a framework that included accelerated Monte Carlo scatter estimation and realistic models of the x-ray source and detector. In the current work, x-ray fluence was held constant across all imaging configurations, corresponding to 0.5 mAs/frame. Performance of circular and elliptical orbits was compared in terms of scatter and scatter-to-primary ratio (SPR) in projections, and contrast, noise, contrast-to-noise ratio (CNR), and truncation (field of view, FOV) in 3D image reconstructions. Results: The highest mean SPR was found in lateral views, ranging from ~5 at ADD of 300 mm to ~1.2 at ADD of 800 mm. Elliptical scans enabled image acquisition with reduced lateral SPR and almost constant SPR across projection angles. The improvement in contrast across the investigated range of air gaps (due to reduction in scatter) was ~2.3x for circular orbits and ~1.9x for elliptical orbits. The increase in noise associated with increased ADD was more pronounced for circular scans (~2x) compared to elliptical scans (~1.5x). The circular orbit with the best CNR performance (ADD=600 mm) yielded ~10% better CNR than the best elliptical orbit (ADD_LAT=600 mm); however, the elliptical orbit increased FOV by ~16%. Conclusion: The flexible imaging geometry of the robotic x-ray system enables development of highly optimized scan orbits. Imaging of the weight-bearing spine could benefit from elliptical detector trajectories to achieve improved tradeoffs in scatter reduction, noise, and truncation.

Proceedings Article | 1 March 2019 Paper

Assessment of measurement deviations: length-extended x-ray imaging for orthopedic applications

Christoph Luckner, Magdalena Herbst, Ludwig Ritschl, Andreas Maier, Steffen Kappler

Proceedings Volume 10948, 1094839 (2019) https://doi.org/10.1117/12.2511507

KEYWORDS: Calibration, Distortion, X-rays, Spine, X-ray imaging, Distance measurement, Radiography

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Proceedings Article | 1 March 2019 Presentation + Paper

Misalignment compensation for ultra-high-resolution and fast CBCT acquisitions

Magdalena Herbst, Christoph Luckner, Julia Wicklein, Jan-Peter Grunz, Tobias Gassenmaier, Ludwig Ritschl, Steffen Kappler

Proceedings Volume 10948, 109481M (2019) https://doi.org/10.1117/12.2513276

KEYWORDS: Image quality, Data acquisition, Image resolution, Visibility, Calibration, Medicine, Diagnostics, X-ray imaging

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SPIE Journal Paper | 5 February 2019 Open Access

Volumetric breast density measurement for personalized screening: accuracy, reproducibility, consistency, and agreement with visual assessment

Andreas Fieselmann, Daniel Förnvik, Hannie Förnvik, Kristina Lång, Hanna Sartor, Sophia Zackrisson, Steffen Kappler, Ludwig Ritschl, Thomas Mertelmeier

JMI, Vol. 6, Issue 03, 031406, (February 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.3.031406

KEYWORDS: Breast, Digital breast tomosynthesis, Tissues, Visualization, Mammography, Breast cancer, Medicine, Magnetic resonance imaging, X-ray imaging, X-rays

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Proceedings Article | 9 March 2018 Paper

Spatio-energetic cross-talk in photon counting detectors: numerical detector model (PcTK) and workflow for CT image quality assessment

Katsuyuki Taguchi, Karl Stierstorfer, Christoph Polster, Okkyun Lee, Steffen Kappler

Proceedings Volume 10573, 1057310 (2018) https://doi.org/10.1117/12.2293881

KEYWORDS: Image quality, X-rays, Sensors, Process modeling, X-ray computed tomography, Photon counting, Systems modeling, 3D modeling, Computed tomography

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Proceedings Article | 9 March 2018 Paper

Spatio-energetic cross-talk in photon counting detectors: N×N binning and sub-pixel masking

Katsuyuki Taguchi, Karl Stierstorfer, Christoph Polster, Okkyun Lee, Steffen Kappler

Proceedings Volume 10573, 105734X (2018) https://doi.org/10.1117/12.2293885

KEYWORDS: Photon counting, Sensors, X-rays, Data modeling, Visibility, Tissues, Distortion, X-ray computed tomography, Tissue optics, Image quality

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SPIE Journal Paper | 16 November 2017

Lung nodule volume quantification and shape differentiation with an ultra-high resolution technique on a photon-counting detector computed tomography system

Wei Zhou, Juan Montoya, Ralf Gutjahr, Andrea Ferrero, Ahmed Halaweish, Steffen Kappler, Cynthia McCollough, Shuai Leng

JMI, Vol. 4, Issue 04, 043502, (November 2017) https://doi.org/10.1117/12.10.1117/1.JMI.4.4.043502

KEYWORDS: Lung, Sensors, Computed tomography, Optical spheres, Stars, Spatial resolution, Photodetectors, Optical computing, Scanners, Statistical analysis

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SPIE Journal Paper | 22 June 2017

Estimation of signal and noise for a whole-body research photon-counting CT system

Zhoubo Li, Shuai Leng, Zhicong Yu, Steffen Kappler, Cynthia McCollough

JMI, Vol. 4, Issue 02, 023505, (June 2017) https://doi.org/10.1117/12.10.1117/1.JMI.4.2.023505

KEYWORDS: Interference (communication), Sensors, Signal attenuation, Photonics systems, Photodetectors, Computed tomography, Mathematical modeling, Signal detection, Beam propagation method, Calibration

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Proceedings Article | 9 March 2017 Paper

Dual energy CT kidney stone differentiation in photon counting computed tomography

R. Gutjahr, C. Polster, A. Henning, S. Kappler, S. Leng, C. McCollough, M. Sedlmair, B. Schmidt, B. Krauss, T. Flohr

Proceedings Volume 10132, 1013237 (2017) https://doi.org/10.1117/12.2252021

KEYWORDS: Renal calculi, Dual energy imaging, Photon counting, Computed tomography, Calcium, Apatite, X-ray imaging, X-rays, Calculi, Curium, X-ray computed tomography, Scanners, Image processing

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Proceedings Article | 9 March 2017 Paper

Ultra-high spatial resolution multi-energy CT using photon counting detector technology

S. Leng, R. Gutjahr, A. Ferrero, S. Kappler, A. Henning, A. Halaweish, W. Zhou, J. Montoya, C. McCollough

Proceedings Volume 10132, 101320Y (2017) https://doi.org/10.1117/12.2255589

KEYWORDS: Dual energy imaging, Photon counting, Sensors, Collimation, Spatial resolution, Computed tomography, Scanners, Renal calculi, Lung, Image resolution, Collimators, Imaging systems

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Proceedings Article | 9 March 2017 Paper

Improving material separation of high-flux whole-body photon counting computed tomography by K-edge pre-filtration

C. Polster, R. Gutjahr, M. Berner, T. Flohr, M. Hertel, S. Kappler, K. Stierstorfer, O. Dietrich

Proceedings Volume 10132, 101320W (2017) https://doi.org/10.1117/12.2254289

KEYWORDS: Photon counting, X-rays, Sensors, X-ray computed tomography, X-ray detectors, Signal detection, Computed tomography, CT reconstruction, Prototyping, Scanners, Hafnium, Iodine, Bone, Photodetectors, Photons, Aluminum

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Proceedings Article | 9 March 2017 Presentation + Paper

Estimating basis line-integrals in spectral distortion-modeled photon counting CT: K-edge imaging using dictionary learning-based x-ray transmittance modeling

Okkyun Lee, Steffen Kappler, Christoph Polster, Katsuyuki Taguchi

Proceedings Volume 10132, 101321A (2017) https://doi.org/10.1117/12.2254663

KEYWORDS: X-rays, Transmittance, Photon counting, Algorithm development, X-ray computed tomography, X-ray detectors, X-ray imaging, Sensors, Data modeling, Gadolinium, Bone

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Proceedings Article | 9 March 2017 Paper

A study of modeling x-ray transmittance for material decomposition without contrast agents

Okkyun Lee, Steffen Kappler, Christoph Polster, Katsuyuki Taguchi

Proceedings Volume 10132, 101323G (2017) https://doi.org/10.1117/12.2254688

KEYWORDS: X-rays, Transmittance, X-ray detectors, Photon counting, Sensors, Performance modeling, Computed tomography, Algorithm development, Bone, Medicine

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Proceedings Article | 9 March 2017 Paper

Renal stone characterization using high resolution imaging mode on a photon counting detector CT system

A. Ferrero, R. Gutjahr, A. Henning, S. Kappler, A. Halaweish, D. Abdurakhimova, Z. Peterson, J. Montoya, S. Leng, C. McCollough

Proceedings Volume 10132, 101323J (2017) https://doi.org/10.1117/12.2255651

KEYWORDS: Imaging systems, Photon counting, Computed tomography, Photodetectors, Image resolution, Renal calculi, Spatial resolution, X-ray computed tomography, X-ray detectors

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Proceedings Article | 9 March 2017 Paper

Lung nodule volume quantification and shape differentiation with an ultra-high resolution technique on a photon counting detector CT system

W. Zhou, J. Montoya, R. Gutjahr, A. Ferrero, A. Halaweish, S. Kappler, C. McCollough, S. Leng

Proceedings Volume 10132, 101323Q (2017) https://doi.org/10.1117/12.2255736

KEYWORDS: Medicine, Lung, Photon counting, Computed tomography, Sensors, Optical spheres, Stars, Spatial resolution, Receivers, Scanners, Cones, Imaging systems

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SPIE Journal Paper | 22 December 2016

Dose-efficient ultrahigh-resolution scan mode using a photon counting detector computed tomography system

Shuai Leng, Zhicong Yu, Ahmed Halaweish, Steffen Kappler, Katharina Hahn, Andre Henning, Zhoubo Li, John Lane, David Levin, Steven Jorgensen, Erik Ritman, Cynthia McCollough

JMI, Vol. 3, Issue 04, 043504, (December 2016) https://doi.org/10.1117/12.10.1117/1.JMI.3.4.043504

KEYWORDS: Sensors, Lung, Spatial resolution, Computed tomography, Photon counting, Scanners, Bone, Modulation transfer functions, Head, Image quality

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SPIE Journal Paper | 14 December 2016

Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner

Zhicong Yu, Shuai Leng, Steffen Kappler, Katharina Hahn, Zhoubo Li, Ahmed F. Halaweish, Andre Henning, Cynthia McCollough

JMI, Vol. 3, Issue 04, 043503, (December 2016) https://doi.org/10.1117/12.10.1117/1.JMI.3.4.043503

KEYWORDS: Sensors, Computed tomography, Photon counting, Scanners, Spatial resolution, Medicine, X-ray computed tomography, X-rays, Data acquisition, Interference (communication)

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SPIE Journal Paper | 18 May 2016 Open Access

Errata: Evaluation of models of spectral distortions in photon-counting detectors for computed tomography

Jochen Cammin, Steffen Kappler, Thomas Weidinger, Katsuyuki Taguchi

JMI, Vol. 3, Issue 02, 029801, (May 2016) https://doi.org/10.1117/12.10.1117/1.JMI.3.2.029801

KEYWORDS: Computed tomography, Spectral models, Photodetectors, Optical computing, Sensors, Medical imaging, Medicine, Physics, Radiology

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SPIE Journal Paper | 6 May 2016

Evaluation of models of spectral distortions in photon-counting detectors for computed tomography

Jochen Cammin, Steffen Kappler, Thomas Weidinger, Katsuyuki Taguchi

JMI, Vol. 3, Issue 02, 023503, (May 2016) https://doi.org/10.1117/12.10.1117/1.JMI.3.2.023503

KEYWORDS: Signal attenuation, Data modeling, Sensors, Gadolinium, Personal protective equipment, Aluminum, Attenuators, Spectral models, X-rays, Photodetectors

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Proceedings Article | 4 April 2016 Paper

Low-dose performance of a whole-body research photon-counting CT scanner

Zhicong Yu, Shuai Leng, Steffen Kappler, Katharina Hahn, Zhoubo Li, Ahmed Halaweish, Andre Henning, Erik Ritman, Cynthia McCollough

Proceedings Volume 9783, 97835Q (2016) https://doi.org/10.1117/12.2217240

KEYWORDS: Computed tomography, Scanners, Photon counting, Image quality, Data acquisition, Modulation transfer functions, X-ray computed tomography, Medicine, Spatial resolution

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Proceedings Article | 25 March 2016 Paper

Spatio-energetic cross-talks in photon counting detectors: detector model and correlated Poisson data generator

Katsuyuki Taguchi, Christoph Polster, Okkyun Lee, Steffen Kappler

Proceedings Volume 9783, 97831R (2016) https://doi.org/10.1117/12.2217133

KEYWORDS: Photon counting, Sensors, Data modeling, X-rays, Monte Carlo methods, Luminescence, Photoelectric effect, X-ray fluorescence spectroscopy, X-ray detectors, Clouds

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Proceedings Article | 25 March 2016 Paper

A high-resolution imaging technique using a whole-body, research photon counting detector CT system

S. Leng, Z. Yu, A. Halaweish, S. Kappler, K. Hahn, A. Henning, Z. Li, J. Lane, D. Levin, S. Jorgensen, E. Ritman, C. McCollough

Proceedings Volume 9783, 97831I (2016) https://doi.org/10.1117/12.2217180

KEYWORDS: Spatial resolution, Modulation transfer functions, Lung, Bone, Photon counting, Sensors, Imaging systems, Computed tomography, Image quality, Scanners, X-ray computed tomography, Heart

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Proceedings Article | 25 March 2016 Paper

Improving material decomposition by spectral optimization of photon counting computed tomography

C. Polster, K. Hahn, R. Gutjahr, F. Schöck, S. Kappler, O. Dietrich, T. Flohr

Proceedings Volume 9783, 97831O (2016) https://doi.org/10.1117/12.2216711

KEYWORDS: Sensors, X-ray detectors, X-rays, Photon counting, Computed tomography, Photodetectors, Mass attenuation coefficient, CT reconstruction, X-ray computed tomography, Image quality standards, Ytterbium, Monte Carlo methods, Bone, Iodine, Thulium

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Proceedings Article | 25 March 2016 Paper

Material decomposition and virtual non-contrast imaging in photon counting computed tomography: an animal study

R. Gutjahr, C. Polster, S. Kappler, H. Pietsch, G. Jost, K. Hahn, F. Schöck, M. Sedlmair, T. Allmendinger, B. Schmidt, B. Krauss, T. Flohr

Proceedings Volume 9783, 97831G (2016) https://doi.org/10.1117/12.2216861

KEYWORDS: Xenon, Lung, X-rays, Tissues, Gadolinium, Sensors, Detection and tracking algorithms, Photon counting, Computed tomography, 3D image enhancement

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Proceedings Article | 25 March 2016 Paper

Estimation of signal and noise for a whole-body photon counting research CT system

Zhoubo Li, Shuai Leng, Zhicong Yu, Steffen Kappler, Cynthia McCollough

Proceedings Volume 9783, 97831F (2016) https://doi.org/10.1117/12.2216637

KEYWORDS: Mathematical modeling, Photon counting, Signal detection, Calibration, Error analysis, Head, Statistical analysis

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Proceedings Article | 18 March 2015 Paper

Photon-counting CT: modeling and compensating of spectral distortion effects

Jochen Cammin, Steffen Kappler, Thomas Weidinger, Katsuyuki Taguchi

Proceedings Volume 9412, 941250 (2015) https://doi.org/10.1117/12.2080849

KEYWORDS: Data modeling, Sensors, Distortion, Gadolinium, Monte Carlo methods, Aluminum, Attenuators, Computed tomography, X-ray computed tomography, Photodetectors

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Proceedings Article | 19 March 2014 Paper

Photon counting CT at elevated X-ray tube currents: contrast stability, image noise and multi-energy performance

S. Kappler, A. Henning, B. Kreisler, F. Schoeck, K. Stierstorfer, T. Flohr

Proceedings Volume 9033, 90331C (2014) https://doi.org/10.1117/12.2043511

KEYWORDS: Sensors, X-rays, X-ray computed tomography, X-ray detectors, X-ray imaging, Photon counting, Scanners, Iodine, Prototyping, Signal detection

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Proceedings Article | 19 March 2014 Paper

Novel iterative reconstruction method for optimal dose usage in redundant CT - acquisitions

H. Bruder, R. Raupach, T. Allmendinger, S. Kappler, J. Sunnegardh, K. Stierstorfer, T. Flohr

Proceedings Volume 9033, 90330P (2014) https://doi.org/10.1117/12.2042985

KEYWORDS: Signal to noise ratio, Composites, Temporal resolution, Computed tomography, Data acquisition, Liver, Modulation transfer functions, Data modeling, Image quality, Spatial resolution

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In CT imaging, a variety of applications exist where reconstructions are SNR and/or resolution limited. However, if the measured data provide redundant information, composite image data with high SNR can be computed. Generally, these composite image volumes will compromise spectral information and/or spatial resolution and/or temporal resolution. This brings us to the idea of transferring the high SNR of the composite image data to low SNR (but high resolution) ‘source’ image data. It was shown that the SNR of CT image data can be improved using iterative reconstruction [1] .We present a novel iterative reconstruction method enabling optimal dose usage of redundant CT measurements of the same body region. The generalized update equation is formulated in image space without further referring to raw data after initial reconstruction of source and composite image data. The update equation consists of a linear combination of the previous update, a correction term constrained by the source data, and a regularization prior initialized by the composite data. The efficiency of the method is demonstrated for different applications: (i) Spectral imaging: we have analysed material decomposition data from dual energy data of our photon counting prototype scanner: the material images can be significantly improved transferring the good noise statistics of the 20 keV threshold image data to each of the material images. (ii) Multi-phase liver imaging: Reconstructions of multi-phase liver data can be optimized by utilizing the noise statistics of combined data from all measured phases (iii) Helical reconstruction with optimized temporal resolution: splitting up reconstruction of redundant helical acquisition data into a short scan reconstruction with Tam window optimizes the temporal resolution The reconstruction of full helical data is then used to optimize the SNR. (iv) Cardiac imaging: the optimal phase image (‘best phase’) can be improved by transferring all applied over radiation into that image. In all these cases, we show that - at constant patient dose - SNR can efficiently be transferred from the composite data to the source data while maintaining spatial, temporal and contrast resolution properties of the source data.

Proceedings Article | 6 March 2013 Paper

Multi-energy performance of a research prototype CT scanner with small-pixel counting detector

S. Kappler, A. Henning, B. Krauss, F. Schoeck, K. Stierstorfer, T. Weidinger, T. Flohr

Proceedings Volume 8668, 86680O (2013) https://doi.org/10.1117/12.2006747

KEYWORDS: Sensors, X-ray computed tomography, Scanners, Iodine, Gadolinium, Calcium, Prototyping, X-rays, Computed tomography, Gold

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Proceedings Article | 6 March 2013 Paper

Threshold optimization for efficient contrast imaging with quantum counting CT detectors

T. Weidinger, T. Buzug, T. Flohr, S. Kappler, F. Schöck, K. Stierstorfer

Proceedings Volume 8668, 86680Q (2013) https://doi.org/10.1117/12.2006518

KEYWORDS: Sensors, X-ray computed tomography, Prototyping, Photon counting, X-rays, Computed tomography, Scanners, Iodine, Image segmentation, Curium

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Proceedings Article | 3 March 2012 Paper

First results from a hybrid prototype CT scanner for exploring benefits of quantum-counting in clinical CT

S. Kappler, T. Hannemann, E. Kraft, B. Kreisler, D. Niederloehner, K. Stierstorfer, T. Flohr

Proceedings Volume 8313, 83130X (2012) https://doi.org/10.1117/12.911295

KEYWORDS: Sensors, X-ray computed tomography, Scanners, X-rays, Prototyping, Computed tomography, Iodine, X-ray detectors, Signal attenuation, Modulation transfer functions

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Proceedings Article | 24 February 2012 Paper

Investigation of ultra low-dose scans in the context of quantum-counting clinical CT

T. Weidinger, T. Buzug, T. Flohr, G. S. Fung, S. Kappler, K. Stierstorfer, B. M. Tsui

Proceedings Volume 8313, 83134B (2012) https://doi.org/10.1117/12.911331

KEYWORDS: Sensors, Electroluminescence, X-ray computed tomography, Electronics, X-rays, Abdomen, Scanners, Denoising, Prototyping, X-ray imaging

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Proceedings Article | 24 February 2012 Paper

Experimental evaluation of the pile-up trigger method in a revised quantum-counting CT detector

E. Kraft, F. Glasser, S. Kappler, D. Niederloehner, P. Villard

Proceedings Volume 8313, 83134A (2012) https://doi.org/10.1117/12.911231

KEYWORDS: Sensors, Calibration, X-rays, X-ray sources, Computed tomography, Computing systems, Signal detection, Image resolution, Electronics, Amplifiers

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Proceedings Article | 16 March 2011 Paper

Quantum-counting CT in the regime of count-rate paralysis: introduction of the pile-up trigger method

S. Kappler, S. Hölzer, E. Kraft, K. Stierstorfer, T. Flohr

Proceedings Volume 7961, 79610T (2011) https://doi.org/10.1117/12.877939

KEYWORDS: X-rays, Sensors, Signal attenuation, X-ray computed tomography, Signal detection, X-ray detectors, X-ray imaging, Computed tomography, Polarization, Scanners

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Proceedings Article | 23 March 2010 Paper

Contrast-enhancement, image noise, and dual-energy simulations for quantum-counting clinical CT

S. Kappler, D. Niederlöhner, K. Stierstorfer, T. Flohr

Proceedings Volume 7622, 76223H (2010) https://doi.org/10.1117/12.843650

KEYWORDS: Sensors, X-ray computed tomography, X-rays, X-ray imaging, Luminescence, Computed tomography, Tin, Scanners, X-ray detectors, Environmental sensing

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Proceedings Article | 22 March 2010 Paper

A research prototype system for quantum-counting clinical CT

S. Kappler, F. Glasser, S. Janssen, E. Kraft, M. Reinwand

Proceedings Volume 7622, 76221Z (2010) https://doi.org/10.1117/12.844238

KEYWORDS: Sensors, X-ray computed tomography, Scanners, X-rays, Prototyping, Signal attenuation, Computed tomography, Quantitative analysis, Electronics, Photon counting

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Proceedings Article | 14 March 2009 Paper

Dual energy with dual source CT and kVp switching with single source CT: a comparison of dual energy performance

M. Grasruck, S. Kappler, M. Reinwand, K. Stierstorfer

Proceedings Volume 7258, 72583R (2009) https://doi.org/10.1117/12.811534

KEYWORDS: Dual energy imaging, Switching, Temporal resolution, Iodine, Sensors, Bone, Scanners, Computed tomography, Modulation, X-rays

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Proceedings Article | 14 March 2009 Paper

Dual-energy performance of dual kVp in comparison to dual-layer and quantum-counting CT system concepts

S. Kappler, M. Grasruck, D. Niederlöhner, M. Strassburg, S. Wirth

Proceedings Volume 7258, 725842 (2009) https://doi.org/10.1117/12.811517

KEYWORDS: Sensors, X-ray computed tomography, Optical filters, X-rays, X-ray detectors, Tin, Radiation effects, Scintillators, Computed tomography, Bone

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Showing 5 of 55 publications

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