Dr. Thomas Buelow Profile

Dr. Thomas Buelow

Sr Scientist at Philips Research

SPIE Involvement:

Author

Publications (30)

Proceedings Article | 3 April 2023 Presentation + Paper

Estimation of incomplete organ-coverage using 3D fully convolutional networks

Hrishikesh Deshpande, Axel Saalbach, Tim Harder, Edna Coetser, Shlomo Gotman, Thomas Buelow, Christian Wülker

Proceedings Volume 12464, 124641E (2023) https://doi.org/10.1117/12.2653986

KEYWORDS: Anatomy, Image segmentation, Education and training, Liver, Image quality, Spleen, Magnetic resonance imaging, Voxels, Kidney, Deep learning

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Proceedings Article | 15 February 2021 Presentation + Paper

Deep learning for the detection of landmarks in head CT images and automatic quality assessment

Hrishikesh Deshpande, Axel Saalbach, Tim Harder, Stewart Young, Thomas Buelow

Proceedings Volume 11596, 115960N (2021) https://doi.org/10.1117/12.2581810

KEYWORDS: Head, Computed tomography, Skull, Scanners, Optical spheres, Neural networks, Medicine, Image segmentation, Automatic control

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Proceedings Article | 15 March 2019 Presentation + Paper

Automatic assessment of the quality of patient positioning and field of view of head CT scans

Thomas Buelow, Stewart Young, Tim Harder, Isabelle Frischmuth, Jan-Hendrik Buhk

Proceedings Volume 10954, 109540N (2019) https://doi.org/10.1117/12.2509823

KEYWORDS: Head, Computed tomography, Bone, Skull, Eye, Image registration, Medicine, Image quality, Scanners, Error analysis, Quality measurement

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Proceedings Article | 18 March 2016 Paper

Surface driven biomechanical breast image registration

Björn Eiben, Vasileios Vavourakis, John Hipwell, Sven Kabus, Cristian Lorenz, Thomas Buelow, Norman Williams, M. Keshtgar, David Hawkes

Proceedings Volume 9786, 97860W (2016) https://doi.org/10.1117/12.2216728

KEYWORDS: Image registration, Breast, Modeling, Magnetic resonance imaging, Natural surfaces, Breast cancer, Tissues, Detection and tracking algorithms, Skin, Computed tomography, Nipple, Surgery

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Proceedings Article | 18 March 2015 Paper

An anatomically oriented breast model for MRI

Dominik Kutra, Martin Bergtholdt, Jörg Sabczynski, Olaf Dössel, Thomas Buelow

Proceedings Volume 9415, 941521 (2015) https://doi.org/10.1117/12.2081851

KEYWORDS: Breast, Magnetic resonance imaging, Breast cancer, 3D image processing, Cancer, 3D modeling, Tissues, Skin, Clocks, Image registration

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Proceedings Article | 17 March 2015 Paper

Inter- and intra-observer variations in the delineation of lesions in mammograms

Thomas Buelow, Harald Heese, Ruediger Grewer, Dominik Kutra, Rafael Wiemker

Proceedings Volume 9416, 941605 (2015) https://doi.org/10.1117/12.2077516

KEYWORDS: Image segmentation, Mammography, Image processing algorithms and systems, Breast, Digital mammography, Clinical research, Medicine, Detection and tracking algorithms, Computer aided diagnosis and therapy, Medical imaging

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Proceedings Article | 24 March 2014 Paper

Identification of corresponding lesions in multiple mammographic views using star-shaped iso-contours

Rafael Wiemker, Dominik Kutra, Harald Heese, Thomas Buelow

Proceedings Volume 9035, 90351A (2014) https://doi.org/10.1117/12.2043218

KEYWORDS: Databases, Breast, Mammography, Computer aided diagnosis and therapy, Image segmentation, Detection and tracking algorithms, Superposition, Algorithm development, Image processing algorithms and systems, Breast cancer

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Proceedings Article | 12 March 2014 Paper

Breast deformation modelling: comparison of methods to obtain a patient specific unloaded configuration

Björn Eiben, Vasileios Vavourakis, John Hipwell, Sven Kabus, Cristian Lorenz, Thomas Buelow, David Hawkes

Proceedings Volume 9036, 903615 (2014) https://doi.org/10.1117/12.2043607

KEYWORDS: Breast, Magnetic resonance imaging, Modeling, Computer simulations, Image segmentation, Protactinium, Medical imaging, In vivo imaging, Data modeling, Chest

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Proceedings Article | 26 February 2013 Paper

Automatic assessment of the quality of patient positioning in mammography

Thomas Bülow, Kirsten Meetz, Dominik Kutra, Thomas Netsch, Rafael Wiemker, Martin Bergtholdt, Jörg Sabczynski, Nataly Wieberneit, Manuela Freund, Ingrid Schulze-Wenck

Proceedings Volume 8670, 867024 (2013) https://doi.org/10.1117/12.2007980

KEYWORDS: Mammography, Nipple, Image quality, Breast, Breast cancer, Image quality standards, Cancer, Tissues, Medical imaging, Detection and tracking algorithms

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Proceedings Article | 14 February 2012 Paper

A multi-dimensional model for localization of highly variable objects

Heike Ruppertshofen, Thomas Bülow, Jens von Berg, Sarah Schmidt, Peter Beyerlein, Zein Salah, Georg Rose, Hauke Schramm

Proceedings Volume 8314, 83142L (2012) https://doi.org/10.1117/12.910900

KEYWORDS: Data modeling, 3D modeling, Hough transforms, Radiography, Bone, 3D image processing, Image processing, Chest, Performance modeling, Medical imaging

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Proceedings Article | 14 February 2012 Paper

Robust estimation of mammographic breast density: a patient-based approach

Harald Heese, Klaus Erhard, Andre Gooßen, Thomas Bulow

Proceedings Volume 8314, 83140T (2012) https://doi.org/10.1117/12.910897

KEYWORDS: Tissues, Breast, Image segmentation, Calibration, Signal attenuation, Data modeling, Breast cancer, Mammography, Image processing, Data acquisition

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Proceedings Article | 4 March 2011 Paper

The impact of motion correction on lesion characterization in DCE breast MR images

Martin Bergtholdt, Sven Kabus, Rafael Wiemker, Thomas Buelow

Proceedings Volume 7963, 79630Z (2011) https://doi.org/10.1117/12.877090

KEYWORDS: Image registration, Image segmentation, Breast, Magnetic resonance imaging, Rigid registration, Tumors, Motion analysis, Computer aided diagnosis and therapy, Image processing algorithms and systems, Visualization

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Proceedings Article | 9 March 2010 Paper

Heterogeneity of kinetic curve parameters as indicator for the malignancy of breast lesions in DCE MRI

Thomas Buelow, Axel Saalbach, Martin Bergtholdt, Rafael Wiemker, Hans Buurman, Lina Arbash Meinel, Gillian Newstead

Proceedings Volume 7624, 76241H (2010) https://doi.org/10.1117/12.844365

KEYWORDS: Image segmentation, Breast, Magnetic resonance imaging, Tumors, Medical research, Scanners, Pathology, Diagnostics, Breast cancer, Tissues

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Proceedings Article | 9 March 2010 Paper

Filter learning and evaluation of the computer aided visualization and analysis (CAVA) paradigm for pulmonary nodules using the LIDC-IDRI database

Rafael Wiemker, Ekta Dharaiya, Amnon Steinberg, Thomas Buelow, Axel Saalbach, Torbjörn Vik

Proceedings Volume 7624, 76242U (2010) https://doi.org/10.1117/12.843797

KEYWORDS: Databases, Lung, Visualization, Image filtering, Computer aided diagnosis and therapy, Visual analytics, Computed tomography, Image segmentation, Image enhancement, Linear filtering

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Proceedings Article | 24 February 2010 Paper

Anatomical modeling of the bronchial tree

Gerrit Hentschel, Tobias Klinder, Thomas Blaffert, Thomas Bülow, Rafael Wiemker, Cristian Lorenz

Proceedings Volume 7625, 76251F (2010) https://doi.org/10.1117/12.844485

KEYWORDS: Lung, Image segmentation, Nomenclature, Chronic obstructive pulmonary disease, Statistical modeling, Computed tomography, Data modeling, Image processing, Detection and tracking algorithms, Algorithm development

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Proceedings Article | 13 March 2009 Paper

Correlation of emphysema score with perceived malignancy of pulmonary nodules: a multi-observer study using the LIDC-IDRI CT lung database

Rafael Wiemker, Thomas Bülow, Thomas Blaffert, Ekta Dharaiya

Proceedings Volume 7263, 726310 (2009) https://doi.org/10.1117/12.811549

KEYWORDS: Emphysema, Lung, Databases, Computed tomography, Computer aided diagnosis and therapy, Signal attenuation, Lung cancer, Solid modeling, Tumor growth modeling, Image analysis

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Proceedings Article | 4 March 2009 Paper

Multi-modality computer-aided diagnosis system for axillary lymph node (ALN) staging: segmentation of ALN on ultrasound images

Lina Arbash Meinel, Martin Bergtholdt, Hiroyuki Abe, D. Huo, Thomas Buelow, Ingwer Carlsen, Gillian Newstead

Proceedings Volume 7260, 72602D (2009) https://doi.org/10.1117/12.811212

KEYWORDS: Aluminum nitride, Image segmentation, Lymphatic system, Ultrasonography, Computer aided diagnosis and therapy, Computing systems, Breast cancer, Magnetic resonance imaging, Francium, Image processing algorithms and systems

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Proceedings Article | 3 March 2009 Paper

Temporal variations in apparent breast lesion volume in dynamic contrast enhanced breast MR imaging

Thomas Buelow, Rafael Wiemker, Lina Arbash Meinel, Hans Buurman, Ursula Kose, Gillian Newstead

Proceedings Volume 7260, 726029 (2009) https://doi.org/10.1117/12.812220

KEYWORDS: Image segmentation, Breast, Magnetic resonance imaging, Image processing algorithms and systems, Tumors, Mammography, Breast cancer, Cancer, Diagnostics, Algorithm development

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Dynamic Contrast Enhanced Breast MR Imaging (DCE BMRI) has emerged as a modality for breast cancer diagnosis. In this modality a temporal sequence of volume images of the breasts is acquired, where a contrast agent is injected after acquisition of the first 3D image. Since the introduction of the modality, research has been directed at the development of computer-aided support for the diagnostic workup. This includes automatic segmentation of mass-like lesions, lesion characterization, and lesion classification. Robustness, user-independence, and reproducibility of the results of computerized methods are essential for such methods to be acceptable for clinical application. A previously proposed and evaluated computerized lesion segmentation method has been further analyzed in this study. The segmentation method uses as input a subtraction image (post-contrast - pre-contrast) and a user defined region of interest (ROI). Previous evaluation studies investigated the robustness of the segmentation against variations in the user selected ROI. Robustness of the method against variations in the image data itself has so far not been investigated. To fill this gap is the purpose of this study. In this study, the segmentation algorithm was applied to a series of subtraction images built from the pre-contrast volume and all available post-contrast image volumes, successively. This provides set of typically 4-5 delineations per lesion, each based on a different phase of the dynamic sequence. Analysis of the apparent lesion volumes derived from these delineations and comparison to manual delineations showed that computerized segmentation is more robust and reproducible than manual segmentation, even if computer segmentations are computed on subtraction images derived from different dynamic phases of the DCE MRI study, while all manual segmentations of a lesion are derived from one and the same dynamic phase of the study. Furthermore, it could be shown that the rate of apparent change of lesion volume over the course of a DCE MRI study is significantly dependent on the lesion type (benign vs. malignant).

Proceedings Article | 17 March 2008 Paper

Repeatability and noise robustness of spicularity features for computer aided characterization of pulmonary nodules in CT

Rafael Wiemker, Roland Opfer, Thomas Bülow, Sven Kabus, Ekta Dharaiya

Proceedings Volume 6915, 691511 (2008) https://doi.org/10.1117/12.765132

KEYWORDS: Computed tomography, Image segmentation, Computer aided diagnosis and therapy, Lung, Image processing, Solids, Natural surfaces, Diagnostics, Medical imaging, Tumors

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Computer aided characterization aims to support the differential diagnosis of indeterminate pulmonary nodules. A number of published studies have correlated automatically computed features from image processing with clinical diagnoses of malignancy vs. benignity. Often, however, a high number of features was trained on a relatively small number of diagnosed nodules, raising a certain skepticism as to how salient and numerically robust the various features really are. On the way towards computer aided diagnosis which is trusted in clinical practice, the credibility of the individual numerical features has to be carefully established. Nodule volume is the most crucial parameter for nodule characterization, and a number of studies are testing its repeatability. Apart from functional parameters (such as dynamic CT enhancement and PET uptake values), the next most widely used parameter is the surface characteristic (vascularization, spicularity, lobulation, smoothness). In this study, we test the repeatability of two simple surface smoothness features which can discriminate between smoothly delineated nodules and those with a high degree of surface irregularity. Robustness of the completely automatically computed features was tested with respect to the following aspects: (a) repeated CT scan of the same patient with equal dose, (b) repeated CT scan with much lower dose and much higher noise, (c) repeated automatic segmentation of the nodules using varying segmentation parameters, resulting in differing nodule surfaces. The tested nodules (81) were all solid or partially solid and included a high number of sub- and juxtapleural nodules. We found that both tested surface characterization features correlated reasonably well with each other (80%), and that in particular the mean-surface-shape-index showed an excellent repeatability: 98% correlation between equal dose CT scans, 93% between standard-dose and low-dose scan (without systematic shift), and 97% between varying HU-threshold of the automatic segmentation, which makes it a reliable feature to be used in computer aided diagnosis.

Proceedings Article | 12 March 2008 Paper

Intuitive parameter-free visualization of tumor vascularization using rotating connectivity projections

Rafael Wiemker, Thomas Bülow, Roland Opfer, Sven Kabus, Ekta Dharaiya

Proceedings Volume 6916, 69161Z (2008) https://doi.org/10.1117/12.765333

KEYWORDS: Tumors, Visualization, Image segmentation, Lung, Computed tomography, Distortion, Binary data, Medical imaging, Image visualization, Optical inspection

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Proceedings Article | 29 March 2007 Paper

Automated hierarchical partitioning of anatomical trees

Rafael Wiemker, Thomas Bülow, Roland Opfer

Proceedings Volume 6511, 65110G (2007) https://doi.org/10.1117/12.705854

KEYWORDS: Image segmentation, 3D image processing, Image filtering, Medical imaging, Image processing algorithms and systems, Lung, Image processing, X-ray computed tomography, Magnetic resonance imaging, X-ray imaging

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Proceedings Article | 29 March 2007 Paper

Segmentation of suspicious lesions in dynamic contrast-enhanced breast MR images

Thomas Bülow, Lina Arbash Meinel, Rafael Wiemker, Ursula Kose, Akiko Shimauchi, Gillian Newstead

Proceedings Volume 6514, 65140T (2007) https://doi.org/10.1117/12.706537

KEYWORDS: Image segmentation, Breast, Magnetic resonance imaging, Computer aided diagnosis and therapy, Breast cancer, Tumors, Feature extraction, Optical spheres, Diagnostics, Data acquisition

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Proceedings Article | 29 March 2007 Paper

Toward computer-aided emphysema quantification on ultralow-dose CT: reproducibility of ventrodorsal gravity effect measurement and correction

Rafael Wiemker, Roland Opfer, Thomas Bülow, Patrik Rogalla, Amnon Steinberg, Ekta Dharaiya, Krishna Subramanyan

Proceedings Volume 6514, 65140O (2007) https://doi.org/10.1117/12.705868

KEYWORDS: Lung, Emphysema, Computed tomography, X-ray computed tomography, Signal attenuation, Tissues, Image segmentation, X-rays, Statistical analysis, Computer aided diagnosis and therapy

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Proceedings Article | 17 March 2006 Paper

Comparative performance analysis for computer-aided lung nodule detection and segmentation on ultra-low-dose vs. standard dose CT

Rafael Wiemker, Patrik Rogalla, Roland Opfer, Ahmet Ekin, Valentina Romano, Thomas Bülow

Proceedings Volume 6146, 614605 (2006) https://doi.org/10.1117/12.649790

KEYWORDS: Computer aided diagnosis and therapy, Computed tomography, Lung, Lung cancer, Detection and tracking algorithms, Computer aided design, Scanners, Visualization, X-ray computed tomography, Feature extraction

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Proceedings Article | 13 March 2006 Paper

Unsupervised extraction and quantification of the bronchial tree on ultra-low-dose vs. standard-dose CT

Rafael Wiemker, Ahmet Ekin, Roland Opfer, Thomas Bülow, Patrik Rogalla

Proceedings Volume 6143, 61432V (2006) https://doi.org/10.1117/12.649530

KEYWORDS: Computed tomography, Optical spheres, X-ray computed tomography, Lung, Scanners, Visualization, 3D image processing, Wavefronts, Wave propagation, Optical inspection

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Proceedings Article | 13 March 2006 Paper

Point based methods for automatic bronchial tree matching and labeling

Thomas Bülow, Cristian Lorenz, Rafael Wiemker, Janett Honko

Proceedings Volume 6143, 61430O (2006) https://doi.org/10.1117/12.650024

KEYWORDS: Data modeling, 3D modeling, Spherical lenses, Image segmentation, Lung, Computed tomography, Shape analysis, Arteries, Medical imaging, Wave propagation

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Proceedings Article | 10 March 2006 Paper

Dedicated registration for DCE MRI mammography

Steffen Renisch, Thomas Bülow, Ingwer Carlsen, Astrid Franz

Proceedings Volume 6144, 61442C (2006) https://doi.org/10.1117/12.651597

KEYWORDS: Image registration, Magnetic resonance imaging, Mammography, Tissues, Data modeling, Data acquisition, Medical imaging, Blood, Optimization (mathematics), 3D image processing

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