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3. Towards Automatic Abdominal Multi-Organ Segmentation in Dual Energy CT using Cascaded 3D Fully Convolutional Network

Author

Chen, Shuqing, Roth, Holger, Dorn, Sabrina, May, Matthias, Cavallaro, Alexander, Lell, Michael M., Kachelrieß, Marc, Oda, Hirohisa, Mori, Kensaku, and Maier, Andreas

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Automatic multi-organ segmentation of the dual energy computed tomography (DECT) data can be beneficial for biomedical research and clinical applications. However, it is a challenging task. Recent advances in deep learning showed the feasibility to use 3-D fully convolutional networks (FCN) for voxel-wise dense predictions in single energy computed tomography (SECT). In this paper, we proposed a 3D FCN based method for automatic multi-organ segmentation in DECT. The work was based on a cascaded FCN and a general model for the major organs trained on a large set of SECT data. We preprocessed the DECT data by using linear weighting and fine-tuned the model for the DECT data. The method was evaluated using 42 torso DECT data acquired with a clinical dual-source CT system. Four abdominal organs (liver, spleen, left and right kidneys) were evaluated. Cross-validation was tested. Effect of the weight on the accuracy was researched. In all the tests, we achieved an average Dice coefficient of 93% for the liver, 90% for the spleen, 91% for the right kidney and 89% for the left kidney, respectively. The results show our method is feasible and promising., Comment: 5 pagens, 4 figures, conference

Published
2017

4. Design and Implementation of a Semantic Dialogue System for Radiologists

Author

Sonntag, Daniel, Huber, Martin, Möller, Manuel, Ndiaye, Alassane, Zillner, Sonja, and Cavallaro, Alexander

Subjects
Computer Science - Human-Computer Interaction, H.5.2
Abstract

This chapter describes a semantic dialogue system for radiologists in a comprehensive case study within the large-scale MEDICO project. MEDICO addresses the need for advanced semantic technologies in the search for medical image and patient data. The objectives are, first, to enable a seamless integration of medical images and different user applications by providing direct access to image semantics, and second, to design and implement a multimodal dialogue shell for the radiologist. Speech-based semantic image retrieval and annotation of medical images should provide the basis for help in clinical decision support and computer aided diagnosis. We will describe the clinical workflow and interaction requirements and focus on the design and implementation of a multimodal user interface for patient/image search or annotation and its implementation while using a speech-based dialogue shell. Ontology modeling provides the backbone for knowledge representation in the dialogue shell and the specific medical application domain; ontology structures are the communication basis of our combined semantic search and retrieval architecture which includes the MEDICO server, the triple store, the semantic search API, the medical visualization toolkit MITK, and the speech-based dialogue shell, amongst others. We will focus on usability aspects of multimodal applications, our storyboard and the implemented speech and touchscreen interaction design.

Published
2017

6. Towards a New Science of a Clinical Data Intelligence

Author

Tresp, Volker, Zillner, Sonja, Costa, Maria J., Huang, Yi, Cavallaro, Alexander, Fasching, Peter A., Reis, Andre, Sedlmayr, Martin, Ganslandt, Thomas, Budde, Klemens, Hinrichs, Carl, Schmidt, Danilo, Daumke, Philipp, Sonntag, Daniel, Wittenberg, Thomas, Oppelt, Patricia G., and Krompass, Denis

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence
Abstract

In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of scientific, i.e., generalizable and reliable results. We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i.e., with data from many patients and with complete patient information. We discuss that Clinical Data Intelligence requires the joint efforts of knowledge engineering, information extraction (from textual and other unstructured data), and statistics and statistical machine learning. We describe some of our main results as conjectures and relate them to a recently funded research project involving two major German university hospitals., Comment: NIPS 2013 Workshop: Machine Learning for Clinical Data Analysis and Healthcare, 2013

Published
2013

20. The THESEUS Use Cases

Author

Kuhlmann, Florian, Hannemann, Jan, Traub, Myriam, Böhme, Christoph, Zillner, Sonja, Cavallaro, Alexander, Seifert, Sascha, Decker, Björn, Traphöner, Ralph, Kayser, Sven, Lindemann, Udo, Prasse, Stefan, Marczinski, Götz, Grützner, Ralf, Fasse, Axel, Oberle, Daniel, Bundy, Alan, Series editor, Gabbay, Dov M., Editor-in-chief, Siekmann, Jörg, Editor-in-chief, Carbonell, Jaime G., Series editor, Pinkal, Manfred, Series editor, Uszkoreit, Hans, Series editor, Veloso, Manuela M., Series editor, Wahlster, Wolfgang, Series editor, Wooldridge, M.J., Series editor, Grallert, Hans-Joachim, editor, Wess, Stefan, editor, Friedrich, Hermann, editor, and Widenka, Thomas, editor

Published
2014
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22. A Discriminative Distance Learning–Based CBIR Framework for Characterization of Indeterminate Liver Lesions

Author

Costa, María Jimena, Tsymbal, Alexey, Hammon, Matthias, Cavallaro, Alexander, Sühling, Michael, Seifert, Sascha, Comaniciu, Dorin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Müller, Henning, editor, Greenspan, Hayit, editor, and Syeda-Mahmood, Tanveer, editor

Published
2012
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23. Medico

Author

Seifert, Sascha, Zillner, Sonja, Huber, Martin, Sintek, Michael, Sonntag, Daniel, Cavallaro, Alexander, Heuser, Lutz, editor, and Wahlster, Wolfgang, editor

Published
2011
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24. 2D Image Registration in CT Images Using Radial Image Descriptors

Author

Graf, Franz, Kriegel, Hans-Peter, Schubert, Matthias, Pölsterl, Sebastian, Cavallaro, Alexander, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Fichtinger, Gabor, editor, Martel, Anne, editor, and Peters, Terry, editor

Published
2011
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25. Region of Interest Queries in CT Scans

Author

Cavallaro, Alexander, Graf, Franz, Kriegel, Hans-Peter, Schubert, Matthias, Thoma, Marisa, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Pfoser, Dieter, editor, Tao, Yufei, editor, Mouratidis, Kyriakos, editor, Nascimento, Mario A., editor, Mokbel, Mohamed, editor, Shekhar, Shashi, editor, and Huang, Yan, editor

Published
2011
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26. Identification of circulating microRNA patterns in patients in psoriasis and psoriatic arthritis

Author

Haschka, Judith, primary, Simon, David, additional, Bayat, Sara, additional, Messner, Zora, additional, Kampylafka, Eleni, additional, Fagni, Filippo, additional, Skalicky, Susanna, additional, Hackl, Matthias, additional, Resch, Heinrich, additional, Zwerina, Jochen, additional, Kleyer, Arnd, additional, Cavallaro, Alexander, additional, Sticherling, Michael, additional, Schett, Goerg, additional, Kocijan, Roland, additional, and Rech, Juergen, additional

Published
2023
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27. Model-Based Esophagus Segmentation from CT Scans Using a Spatial Probability Map

Author

Feulner, Johannes, Kevin Zhou, S., Huber, Martin, Cavallaro, Alexander, Hornegger, Joachim, Comaniciu, Dorin, Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Jiang, Tianzi, editor, Navab, Nassir, editor, Pluim, Josien P. W., editor, and Viergever, Max A., editor

Published
2010
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28. Combining Patient Metadata Extraction and Automatic Image Parsing for the Generation of an Anatomic Atlas

Author

Möller, Manuel, Ernst, Patrick, Sintek, Michael, Seifert, Sascha, Grimnes, Gunnar, Cavallaro, Alexander, Dengel, Andreas, Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Goebel, Randy, Siekmann, Jörg, Wahlster, Wolfgang, Setchi, Rossitza, editor, Jordanov, Ivan, editor, Howlett, Robert J., editor, and Jain, Lakhmi C., editor

Published
2010
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29. Fast Automatic Segmentation of the Esophagus from 3D CT Data Using a Probabilistic Model

Author

Feulner, Johannes, Zhou, S. Kevin, Cavallaro, Alexander, Seifert, Sascha, Hornegger, Joachim, Comaniciu, Dorin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Yang, Guang-Zhong, editor, Hawkes, David, editor, Rueckert, Daniel, editor, Noble, Alison, editor, and Taylor, Chris, editor

Published
2009
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32. The Clinical Data Intelligence Project: A smart data initiative

Author

Sonntag, Daniel, Tresp, Volker, Zillner, Sonja, Cavallaro, Alexander, Hammon, Matthias, Reis, André, Fasching, Peter A., Sedlmayr, Martin, Ganslandt, Thomas, Prokosch, Hans-Ulrich, Budde, Klemens, Schmidt, Danilo, Hinrichs, Carl, Wittenberg, Thomas, Daumke, Philipp, and Oppelt, Patricia G.

Published
2016
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35. Mammographic density as a risk factor for breast cancer in a German case–control study

Author

Heusinger, Katharina, Loehberg, Christian R., Haeberle, Lothar, Jud, Sebastian M., Klingsiek, Peter, Hein, Alexander, Bayer, Christian M., Rauh, Claudia, Uder, Michael, Cavallaro, Alexander, May, Matthias S., Adamietz, Boris, Schulz-Wendtland, Ruediger, Wittenberg, Thomas, Wagner, Florian, Beckmann, Matthias W., and Fasching, Peter A.

Published
2011

36. Serum miRNAs unterstützen die Entscheidungsfindung bezüglich einer Prostatastanzbiopsie speziell bei Patienten mit niedrigen PI-RADS scores

Author

Keck, Bastian, Borkowetz, Angelika, Poellmann, Julia, Jansen, Thilo, Fischer, Moritz, Fuessel, Susanne, Kahlmeyer, Andreas, Wirth, Manfred, Huber, Johannes, Cavallaro, Alexander, Hammon, Matthias, Platzek, Ivan, Hartmann, Arndt, Baretton, Gustavo, Kunath, Frank, Sikic, Danijel, Taubert, Helge, Wullich, Bernd, Erdmann, Kati, and Wach, Sven

Subjects
ddc: 610, Medicine and health
Abstract

Einleitung: Das multiparametrische MRT und MRT-gesteuerte, gezielte Stanzbiopsien sind in der Lage, die Detektionsraten von Prostatakarzinomen deutlich zu verbessern. Jedoch bleibt eine Vorhersage, mit welcher Wahrscheinlichkeit ein klinisch signifikantes Karzinom vorliegt allein auf Basis von klinischen [zum vollständigen Text gelangen Sie über die oben angegebene URL]

Published
2022
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45. Serum miRNAs Support the Indication for MRI-Ultrasound Fusion-Guided Biopsy of the Prostate in Patients with Low-PI-RADS Lesions

Author

Keck, Bastian, Borkowetz, Angelika, Poellmann, Julia, Jansen, Thilo, Fischer, Moritz, Fuessel, Susanne, Kahlmeyer, Andreas, Wirth, Manfred, Huber, Johannes, Cavallaro, Alexander, Platzek, Matthias Hammon Ivan, Hartmann, Arndt, Baretton, Gustavo, Kunath, Frank, Sikic, Danijel, Taubert, Helge, Wullich, Bernd, Erdmann, Kati, and Wach, Sven

Subjects
microRNA, diagnosis, mpMRI, prostate biopsy, prostate cancer, miRNA, PI-RADS
Abstract

Multiparametric MRI (mpMRI) and targeted biopsy of the prostate enhance the tumor detection rate. However, the prediction of clinically significant prostate cancer (PCa) is still limited. Our study tested the additional value of serum levels of selected miRNAs in combination with clinical and mpMRI information for PCa prediction and classification. A total of 289 patients underwent targeted mpMRI-ultrasound fusion-guided prostate biopsy complemented by systematic biopsy. Serum miRNA levels of miRNAs (miR-141, miR-375, miR-21-5p, miR-320b, miR-210-3p, let-7c, and miR-486) were determined by quantitative PCR. Detection of any PCa and of significant PCa were the outcome variables. The patient age, pre-biopsy PSA level, previous biopsy procedure, PI-RADS score, and serum miRNA levels were covariates for regularized binary logistic regression models. The addition of miRNA expression of miR-486 and let-7c to the baseline model, containing only clinical parameters, increased the predictive accuracy. Particularly in patients with PI-RADS ≤3, we determined a sensitivity for detecting significant PCa (Gleason score≥7a corresponding to Grade group ≥2) of 95.2%, and an NPV for absence of significant PCa of 97.1%. This accuracy could be useful to support patient counseling in selected cases.

Published
2021
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48. Magnetresonanztomographie für die stereotaktische Strahlentherapie des Gehirns

Author

Putz, Florian, Mengling, Veit, Perrin, Rosalind, Masitho, Siti, Weissmann, Thomas, Rösch, Johannes, Bäuerle, Tobias, Janka, Rolf, Cavallaro, Alexander, Uder, Michael, Amarteifio, Patrick, Doussin, Sylvain, Schmidt, Manuel Alexander, Dörfler, Arndt, Semrau, Sabine, Lettmaier, Sebastian, Fietkau, Rainer, and Bert, Christoph

Subjects
ddc:610
Abstract

Due to its superior soft tissue contrast, magnetic resonance imaging (MRI) is essential for many radiotherapy treatment indications. This is especially true for treatment planning in intracranial tumors, where MRI has a long-standing history for target delineation in clinical practice. Despite its routine use, care has to be taken when selecting and acquiring MRI studies for the purpose of radiotherapy treatment planning. Requirements on MRI are particularly demanding for intracranial stereotactic radiotherapy, where accurate imaging has a critical role in treatment success. However, MR images acquired for routine radiological assessment are frequently unsuitable for high-precision stereotactic radiotherapy as the requirements for imaging are significantly different for radiotherapy planning and diagnostic radiology. To assure that optimal imaging is used for treatment planning, the radiation oncologist needs proper knowledge of the most important requirements concerning the use of MRI in brain stereotactic radiotherapy. In the present review, we summarize and discuss the most relevant issues when using MR images for target volume delineation in intracranial stereotactic radiotherapy.

Published
2020

49. The THESEUS Use Cases

Author

Kuhlmann, Florian, primary, Hannemann, Jan, additional, Traub, Myriam, additional, Böhme, Christoph, additional, Zillner, Sonja, additional, Cavallaro, Alexander, additional, Seifert, Sascha, additional, Decker, Björn, additional, Traphöner, Ralph, additional, Kayser, Sven, additional, Lindemann, Udo, additional, Prasse, Stefan, additional, Marczinski, Götz, additional, Grützner, Ralf, additional, Fasse, Axel, additional, and Oberle, Daniel, additional

Published
2014
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