Prof. Martin Fiebich Profile

Prof. Martin Fiebich

Professor at Technische Hochschule Mittelhessen

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Author

Publications (29)

Proceedings Article | 22 May 2020 Paper

Concept to extend anthropomorphic breast phantoms for 2D digital mammography with movable lesions at variable reproducible positions

Ulf Mäder, Martin Fiebich, Karin Bock, Stephan Schopphoven

Proceedings Volume 11513, 115131L (2020) https://doi.org/10.1117/12.2560619

KEYWORDS: Mammography, Breast, Digital mammography, Image quality, Databases, Diagnostics, Image acquisition, Imaging systems, 3D printing

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Proceedings Article | 15 March 2019 Paper

3D-printable lung substitutes for particle therapy on the base of high-resolution CTs for mimicking Bragg peak degradation

Kilian Baumann, Ulrich Weber, Martin Fiebich, Klemens Zink, Ulf Mäder

Proceedings Volume 10954, 1095414 (2019) https://doi.org/10.1117/12.2512742

KEYWORDS: Lung, Tissues, Modulation, Particles, Computed tomography, Monte Carlo methods, Binary data, Physics, Biology, Medicine, 3D printing

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Proceedings Article | 15 March 2019 Presentation + Paper

Automatically estimating size information for dose management systems applied in fluoroscopy and radiography

Alexander Neißner, Petar Penchev, Ulf Mäder, Andreas Mahnken, Martin Fiebich

Proceedings Volume 10954, 1095403 (2019) https://doi.org/10.1117/12.2512784

KEYWORDS: Calibration, Monte Carlo methods, Sensors, Radiography, Fluoroscopy, Data modeling, Spine, X-rays, Scattering, Diagnostics

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Proceedings Article | 30 March 2016 Paper

Physical properties of a new flat panel detector with cesium-iodide technology

Andreas Hahn, Petar Penchev, Martin Fiebich

Proceedings Volume 9783, 97833V (2016) https://doi.org/10.1117/12.2216829

KEYWORDS: Sensors, Modulation transfer functions, Standards development, Radiography, Crystals, Electronics, Automatic exposure, X-ray detectors, X-rays, Scintillators, Quantum efficiency, Picture Archiving and Communication System

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Proceedings Article | 18 March 2015 Paper

Reduction of iodinated contrast medium in CT: feasibility study

Radin Nasirudin, Kai Mei, Felix Kopp, Petar Penchev, Ernst Rummeny, Martin Fiebich, Peter Noël

Proceedings Volume 9412, 94122L (2015) https://doi.org/10.1117/12.2082143

KEYWORDS: Iodine, Reconstruction algorithms, Image enhancement, Curium, Diagnostics, Photons, Sensors, Image quality, Image restoration, Monte Carlo methods

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Proceedings Article | 19 March 2014 Paper

Physical properties of a new flat panel detector with irradiated side sampling (ISS) technology

Martin Fiebich, Jan Burg, Christina Piel, Laura Rodenheber, Petar Penchev, Gabriele Krombach

Proceedings Volume 9033, 90333U (2014) https://doi.org/10.1117/12.2043736

KEYWORDS: Sensors, Modulation transfer functions, X-rays, X-ray detectors, Absorption, Light scattering, Crystals, Picture Archiving and Communication System, Quantum efficiency, Standards development

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Proceedings Article | 19 March 2014 Paper

A comparison of simulation tools for photon-counting spectral CT

Radin Nasirudin, Petar Penchev, Kai Mei, Ernst Rummeny, Martin Fiebich, Peter Noël

Proceedings Volume 9033, 90334W (2014) https://doi.org/10.1117/12.2043538

KEYWORDS: Monte Carlo methods, Image quality, X-ray computed tomography, Sensors, X-rays, Photodetectors, Computer simulations, Iodine, Scanners, Target detection

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Proceedings Article | 6 March 2013 Paper

Characterization of spectral x-ray imaging for dental cone-beam computed tomography

Radin Adi Aizudin Bin Radin Nasirudin, Petar Penchev, Kai Mei, Ernst Rummeny, Martin Fiebich, Peter Noël

Proceedings Volume 8668, 86684S (2013) https://doi.org/10.1117/12.2008072

KEYWORDS: Monte Carlo methods, Gold, Metals, Sensors, Reconstruction algorithms, Signal attenuation, Image quality, X-ray computed tomography, Computed tomography, X-ray imaging

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SPIE Journal Paper | 1 October 2012 Open Access

Evaluation and quantification of spectral information in tissue by confocal microscopy

Ulf Maeder, Kay Marquardt, Sebastian Beer, Thorsten Bergmann, Thomas Schmidts, Johannes Heverhagen, Klemens Zink, Frank Runkel, Martin Fiebich

JBO, Vol. 17, Issue 10, 106011, (October 2012) https://doi.org/10.1117/12.10.1117/1.JBO.17.10.106011

KEYWORDS: Skin, Tissues, Confocal microscopy, In vivo imaging, Image processing, Visualization, In vitro testing, Tissue optics, Luminescence, Microscopy

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Proceedings Article | 3 March 2012 Paper

A new phantom for image quality, geometric destortion, and HU calibration in MSCT and CBCT

Johannes Voigt, Christian Blendl, Markus Selbach, Clemens Uphoff, Martin Fiebich

Proceedings Volume 8313, 83132P (2012) https://doi.org/10.1117/12.911611

KEYWORDS: Modulation transfer functions, Optical spheres, Image quality, Calibration, Aluminum, Computed tomography, 3D image processing, Radiotherapy, 3D acquisition, Signal to noise ratio

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Flat panel cone-beam computed tomography (CBCT) is developing to the state-of-the-art technique in several medical disciplines such as dental and otorhinolaryngological imaging. Dental and otorhinolaryngological CBCT systems offer a variety of different field-of-view sizes from 6.0 to 17.0 cm. Standard phantoms are only designed for the use in multi-slices CT (MSCT) and there is no phantom which provides detail structures for all common characteristic values and Hounsfield calibration. In this study we present a new phantom specially designed for use with MSCT and CBCT systems providing detail structures for MTF, 3D MTF, NPS, SNR, geometric distortion and HU calibration. With this phantom you'll only need one acquisition for image quality investigation and assurance. Materials and methods: The phantom design is shown in figure 1. To investigate the practicability, the phantom was scanned using dedicated MSCT-scanners, 3D C-arms und digital volume tomographs. The acquired axial image stacks were analyzed using a dedicated computer program, which is provided as an ImageJ plugin. The MTF was compared to other methodologies such as a thin wire, a sphere or noise response [10, 13, 14]. The HU values were also computed using other common methods. Results: These results are similar to the results of others studies [10, 13, 14]. The method has proven to be stable and delivers comparable results to other methodologies such as using a thin wire. The NPS was calculated for all materials. Furthermore, CT numbers for all materials were computed and compared to the desired values. The measurement of geometric deformation has proven to be accurate. Conclusion: A unique feature of this phantom is to compute the geometric deformation of the 3D-volume image. This offers the chance to improve accuracy, e.g. in dental implant planning. Another convenient feature is that the phantom needs to be scanned only once with otorhinolaryngological volume tomographs to be fully displayed. It is shown, that this new phantom provides amazing potential for image quality assurance in MSCT as well as in CBCT. It contains detail structures for all characteristic image quality values. In combination with a software tool it is the silver bullet for image quality assurance.

Proceedings Article | 9 February 2012 Paper

Spectrally resolved visualization of fluorescent dyes permeating into skin

Ulf Maeder, Thorsten Bergmann, Sebastian Beer, Jan Michael Burg, Thomas Schmidts, Frank Runkel, Martin Fiebich

Proceedings Volume 8225, 822523 (2012) https://doi.org/10.1117/12.907815

KEYWORDS: Skin, Tissues, Confocal microscopy, Imaging systems, Diffusion, Luminescence, Visualization, Microscopes, Imaging spectroscopy, Image segmentation

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Proceedings Article | 3 February 2012 Paper

Quantifying fluorescence signals in confocal image stacks deep in turbid media

S. Beer, U. Maeder, T. Bergmann, J. Burg, M. Fiebich, F. Runkel

Proceedings Volume 8227, 82271G (2012) https://doi.org/10.1117/12.907875

KEYWORDS: Signal attenuation, Luminescence, Confocal microscopy, Particles, Scattering, Absorption, Skin, Image processing, Light scattering, Microscopes

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Proceedings Article | 2 February 2012 Paper

Fluorescent nanodiamonds as highly stable biomarker for endotoxin verification

Thorsten Bergmann, Jan Michael Burg, Maria Lilholt, Ulf Maeder, Sebastian Beer, Denise Salzig, Mehrdad Ebrahimi, Peter Czermak, Martin Fiebich

Proceedings Volume 8233, 82331H (2012) https://doi.org/10.1117/12.909251

KEYWORDS: Neodymium, Luminescence, Particles, Confocal microscopy, Visualization, Diamond, Proteins, Applied sciences, In vitro testing, In vivo imaging

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Proceedings Article | 9 June 2011 Paper

Calibration phantom for the quantification of fluorescent labels in deep skin tissue

Sebastian Beer, Ulf Maeder, Thorsten Bergmann, Peggy Schlupp, Thomas Schmidts, Johannes Heverhagen, Frank Runkel, Martin Fiebich

Proceedings Volume 8086, 80861L (2011) https://doi.org/10.1117/12.889973

KEYWORDS: Skin, Luminescence, Scattering, Signal attenuation, Calibration, Fluorescent markers, Tissues, Absorption, Confocal microscopy, Microscopes

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Proceedings Article | 9 June 2011 Paper

4D confocal microscopy method for drug localization in the skin

Ulf Maeder, Thorsten Bergmann, Jan Michael Burg, Sebastian Beer, Peggy Schlupp, Thomas Schmidts, Johannes Heverhagen, Frank Runkel, Martin Fiebich

Proceedings Volume 8086, 80861A (2011) https://doi.org/10.1117/12.889497

KEYWORDS: Skin, Confocal microscopy, Tissues, Signal detection, Microscopes, Luminescence, Scattering, Applied sciences, Detector development, Systems modeling

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Proceedings Article | 17 March 2011 Paper

Comparing image quality and radiation dose between new generation MDCT and CBCT systems

Omar Sultan, Martin Fiebich, Martin Dobritz, Bernhard Renger, Ernst Rummeny, Peter Noël

Proceedings Volume 7961, 79615U (2011) https://doi.org/10.1117/12.878039

KEYWORDS: Image quality, Spatial resolution, Computed tomography, Image quality standards, Imaging systems, Bone, Tissues, Sensors, Visualization, Diagnostics

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Proceedings Article | 9 March 2011 Paper

Preliminary clinical results: an analyzing tool for 2D optical imaging in detection of active inflammation in rheumatoid arthritis

Radin Adi Aizudin Bin Radin Nasirudin, Reinhard Meier, Carmen Ahari, Matti Sievert, Martin Fiebich, Ernst Rummeny, Peter Noël

Proceedings Volume 7965, 796512 (2011) https://doi.org/10.1117/12.878021

KEYWORDS: Image fusion, Inflammation, Magnetic resonance imaging, Image analysis, Optical imaging, Diagnostics, Software development, X-ray imaging, X-rays, Luminescence

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Proceedings Article | 11 February 2011 Paper

Development of a skin phantom of the epidermis and evaluation by using fluorescence techniques

Thorsten Bergmann, Sebastian Beer, Ulf Maeder, Jan Burg, Peggy Schlupp, Thomas Schmidts, Frank Runkel, Martin Fiebich

Proceedings Volume 7906, 79060T (2011) https://doi.org/10.1117/12.874676

KEYWORDS: Skin, Luminescence, Scattering, Confocal microscopy, Microscopes, Tissue optics, Laser scattering, Fluorescence spectroscopy, Optical properties, Spectroscopy

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Proceedings Article | 10 February 2011 Paper

Studying skin penetration by NMR imaging

J. M. Burg, M. Voelker, P. Schlupp, T. Schmidts, U. Maeder, T. Bergmann, F. Runkel, J. Heverhagen, M. Fiebich

Proceedings Volume 7892, 78920V (2011) https://doi.org/10.1117/12.874886

KEYWORDS: Skin, Magnetic resonance imaging, Visualization, Imaging systems, Tissues, Scanners, Microscopy, Tissue optics, Visual analytics, Visual process modeling

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Proceedings Article | 9 March 2010 Paper

Hardware and software system for automatic microemulsion assay evaluation by analysis of optical properties

Ulf Maeder, Thomas Schmidts, Jan-Michael Burg, Johannes Heverhagen, Frank Runkel, Martin Fiebich

Proceedings Volume 7626, 762625 (2010) https://doi.org/10.1117/12.845489

KEYWORDS: Cameras, Optical properties, Image processing, Transparency, Visualization, Skin, Image analysis, Aluminum, Information visualization, Calibration

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Proceedings Article | 4 March 2009 Paper

Automated lung nodule detection and segmentation

Christian Schneider, Azad Amjadi, Anja Richter, Martin Fiebich

Proceedings Volume 7260, 72601T (2009) https://doi.org/10.1117/12.811985

KEYWORDS: Lung, Image segmentation, Detection and tracking algorithms, Spherical lenses, Lung cancer, Chest, Edge detection, Image processing algorithms and systems, CAD systems, Computer aided diagnosis and therapy

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Proceedings Article | 3 July 2001 Paper

Improvement of method for computer-assisted detection of pulmonary nodules in CT of the chest

Martin Fiebich, Dag Wormanns, Walter Heindel

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431147

KEYWORDS: Computer aided diagnosis and therapy, Lung, Chest, Image segmentation, Computed tomography, Tissues, Lung cancer, CAD systems, Visualization, Silicon

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Proceedings Article | 28 May 2001 Paper

Clinical experience with a computer-aided diagnosis system for automatic detection of pulmonary nodules at spiral CT of the chest

Dag Wormanns, Martin Fiebich, Mustafa Saidi, Stefan Diederich, Walter Heindel

Proceedings Volume 4319, (2001) https://doi.org/10.1117/12.428047

KEYWORDS: Computer aided diagnosis and therapy, CAD systems, Lung, Image segmentation, Computed tomography, Chest, Lung cancer, Feature extraction, Detection and tracking algorithms, Computer aided design

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Proceedings Article | 6 June 2000 Paper

Automatic detection of pulmonary nodules at spiral CT: first clinical experience with a computer-aided diagnosis system

Dag Wormanns, Martin Fiebich, Christian Wietholt, Stefan Diederich, Walter Heindel

Proceedings Volume 3979, (2000) https://doi.org/10.1117/12.387608

KEYWORDS: CAD systems, Computed tomography, Computer aided diagnosis and therapy, Detection and tracking algorithms, Feature extraction, Image segmentation, Computing systems, Chest, Algorithm development, Lung

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Proceedings Article | 21 May 1999 Paper

Automatic detection of pulmonary nodules in low-dose screening thoracic CT examinations

Martin Fiebich, Christian Wietholt, Bernhard Renger, Samuel Armato, Kenneth Hoffmann, Dag Wormanns, Stefan Diederich

Proceedings Volume 3661, (1999) https://doi.org/10.1117/12.348543

KEYWORDS: Lung, Chest, Computed tomography, Tissues, Lung cancer, Feature extraction, Image segmentation, Collimation, Visualization, Image processing

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Proceedings Article | 24 June 1998 Paper

Automated centerline tracking of the human colon

Yaseen Samara, Martin Fiebich, Abraham Dachman, Kunio Doi, Kenneth Hoffmann

Proceedings Volume 3338, (1998) https://doi.org/10.1117/12.310953

KEYWORDS: Colon, Colorectal cancer, Rectum, Cancer, Computed tomography, Virtual colonoscopy, Fiber optics, Inspection, Intestine, Lung cancer

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Proceedings Article | 24 June 1998 Paper

Fast semiautomatic techniques for segmentation of cranial vessels in CT angiographic studies

Martin Fiebich, Bernhard Renger, Vivek Sehgal, Christopher Straus, Kenneth Hoffmann

Proceedings Volume 3338, (1998) https://doi.org/10.1117/12.310829

KEYWORDS: Bone, Image segmentation, 3D modeling, Angiography, 3D image processing, Computed tomography, Visualization, Pathology, Skull, Image visualization

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Proceedings Article | 25 April 1997 Paper

Computer-assisted diagnosis in CT angiography of abdominal aortic aneurysms

Martin Fiebich, Myrosia Tomiak, Roger Engelmann, James McGill, Kenneth Hoffmann

Proceedings Volume 3034, (1997) https://doi.org/10.1117/12.274087

KEYWORDS: Image segmentation, Bone, Digital filtering, Angiography, 3D vision, 3D modeling, Image filtering, Visualization, Computed tomography, Arteries

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The purpose of this study was to develop methods for automatic 3D-segmentation and automatic quantification of vascular structures in CT angiographic studies, e.g., abdominal aortic aneurysms. Methods for segmentation were developed based on thresholding, maximum gradient, and second derivative techniques. All parameters for the segmentation are generated automatically, i.e. no user interaction is necessary for this process. Median filtering of all images is initially performed to reduce the image noise. The algorithm then automatically identifies the starting point inside the aorta for the volume growing. The segmentation of the vascular tree is achieved in two steps. First, only the aorta and small parts of branch vessels are segmented by using strong restrictions in the parameters for threshold and gradient. A description of the aorta is generated by fitting the detected outer border of the aorta with an ellipse. This description includes centerline, direction, contour, eccentricity, and area. In the second step, segmentation parameters are changed automatically for segmentation of branch vessels. A shaded surface display of the segmented structures is then generated. The segmentation of the aorta appears accurate, is fast, and the 3D display can be manipulated in real time. The quantitative description of the aorta is reliable giving reproducible information. Total CPU time for the segmentation and description is less than five minutes on a standard workstation. Time-consuming manual segmentation and parameterization of vascular structures are obviated, with 3D visualization and quantitative results available in minutes instead of hours. This technique for segmentation and description of the aorta and renal arteries shows the feasibility of computer assisted diagnosis in CT angiographic studies without user interaction. Besides the description, a rapid 3D view of the vessels is generated, often needed by the physician and normally only achievable by time consuming manual segmentation.

Proceedings Article | 25 April 1997 Paper

Analysis of 3D motion of in-vivo pacemaker leads

Kenneth Hoffmann, Benjamin Williams, Jacqueline Esthappan, Shiuh-Yung Chen, Martin Fiebich, John Carroll, Hajime Harauchi, Vince Doerr, G. Neal Kay, Allen Eberhardt, Mary Overland

Proceedings Volume 3034, (1997) https://doi.org/10.1117/12.274145

KEYWORDS: Lead, In vivo imaging, 3D acquisition, 3D image processing, Imaging systems, Motion analysis, Calibration, Electrodes, Failure analysis, Image acquisition

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In vivo analyses of pacemaker lead motion during the cardiac cycle have become important due to incidences of failure of some of the components. For the calculation and evaluation of in vivo stresses in pacemaker leads, the 3D motion of the lead must be determined. To accomplish this, we have developed a technique for calculation of the overall and relative 3D position, and thereby the 3D motion, of in vivo pacemaker leads through the cardiac cycle.Biplane image sequences of patients with pacemakers were acquired for at least two cardiac cycles. After the patient acquisitions, biplane images of a calibration phantom were obtained. The biplane imaging geometries were calculated from the images of the calibration phantom. Points on the electrodes and the lead centerlines were indicated manually in all acquired images. The indicated points along the leads were then fit using a cubic spline. In each projection, the cumulative arclength along the centerlines in two temporally adjacent images was used to identify corresponding points along the centerlines. To overcome the non-synchronicity of the biplane image acquisition, temporal interpolation was performed using these corresponding points based on a linear scheme. For each time point, corresponding points along the lead centerlines in the pairs of biplane images were identified using epipolar lines. The 3D lead centerlines were calculated from the calculated imaging geometries and the corresponding image points along the lead centerlines. From these data, 3D lead motion and the variations of the lead position with time were calculated and evaluated throughout the cardiac cycle. The reproducibility of the indicated lead centerlines was approximately 0.3 mm. The precision of the calculated rotation matrix and translation vector defining image geometry were approximately 2 mm. 3D positions were reproducible to within 2 mm. Relative positional errors were less than 0.3 mm. Lead motion correlated strongly with phases of the cardiac cycle. Our results indicate that complex motions of in vivo pacemaker leads can be precisely determined. Thus, we believe that this technique will provide precise 3D motion and shapes on which to base subsequent stress analysis of pacemaker lead components.

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