@inproceedings{PalmSchollLehmannetal., author = {Palm, Christoph and Scholl, Ingrid and Lehmann, Thomas M. and Spitzer, Klaus}, title = {Nutzung eines Farbkonstanz-Algorithmus zur Entfernung von Glanzlichtern in laryngoskopischen Bildern}, series = {Methoden der Medizinischen Informatik, Biometrie und Epidemiologie in der modernen Informationsgesellschaft}, booktitle = {Methoden der Medizinischen Informatik, Biometrie und Epidemiologie in der modernen Informationsgesellschaft}, editor = {Greiser, E. and Wischnewsky, M.}, publisher = {MMV Medien und Medizin}, address = {M{\"u}nchen}, isbn = {9783820813357}, pages = {300 -- 303}, abstract = {1 Einf{\"u}hrung Funktionelle und organische St{\"o}rungen im Larynx beeintr{\"a}chtigen die Ausdrucksf{\"a}higkeit des Menschen. Zur Diagnostik und Verlaufkontrolle werden die Stimmlippen im Larynx mit Hilfe der Video-Laryngoskopie aufgenommen. Zur optimalen Farbmessung wird dazu an das Lupenendoskop eine 3-Chip-CCD-Kamera angeschlossen, die eine unabh{\"a}ngige Aufnahme der drei Farbkan{\"a}le erlaubt. Die bisherige subjektive Befundung ist von der Erfahrung des Untersuchers abh{\"a}ngig und l{\"a}ßt nur eine grobe Klassifikation der Krankheitsbilder zu. Zur Objektivierung werden daher quantitative Parameter f{\"u}r Farbe, Textur und Schwingung entwickelt. Neben dem Einfluß der wechselnden Lichtquellenfarbe auf den Farbeindruck ist die Sekretauflage auf den Stimmlippen ein Problem bei der Farb-und Texturanalyse. Sie kann zu ausgedehnten Glanzlichtern f{\"u}hren und so weite Bereiche der Stimmlippen f{\"u}r die Farb-und Texturanalyse unbrauchbar machen. Dieser Beitrag stellt einen Farbkonstanz-Algorithmus vor, der unabh{\"a}ngig von der Lichtquelle quantitative Farbwerte des Gewebes liefert und die Glanzlichtdetektion und -elimination erm{\"o}glicht. 2 Methodik Ziel des Farbkonstanz-Algorithmus ist die Trennung von Lichtquellen-und Gewebefarbe. Unter Verwendung des dichromatischen Reflexionsmodells [1] kann die Oberfl{\"a}chenreflexion mit der Farbe der Lichtquelle und die K{\"o}rperreflexion mit der Gewebefarbe identifiziert werden. Der Farbeindruck entsteht aus der Linearkombination beider Farbkomponenten. Ihre Gewichtung ist von der Aufnahmegeometrie abh{\"a}ngig, insbesondere vom Winkel zwischen Oberfl{\"a}chennormalen und dem Positionsvektor der Lichtquelle. In einem zweistufigen Verfahren wird zun{\"a}chst die Lichtquellenfarbe gesch{\"a}tzt, dann die Gewebefarbe ermittelt. Hieraus k{\"o}nnen beide Farbanteile durch die Berechnung der Gewichtsfaktoren pixelweise getrennt werden.}, language = {de} } @article{Palm, author = {Palm, Christoph}, title = {Color Texture Classification by Integrative Co-Occurrence Matrices}, series = {Pattern Recognition}, volume = {37}, journal = {Pattern Recognition}, number = {5}, doi = {10.1016/j.patcog.2003.09.010}, pages = {965 -- 976}, abstract = {Integrative Co-occurrence matrices are introduced as novel features for color texture classification. The extended Co-occurrence notation allows the comparison between integrative and parallel color texture concepts. The information profit of the new matrices is shown quantitatively using the Kolmogorov distance and by extensive classification experiments on two datasets. Applying them to the RGB and the LUV color space the combined color and intensity textures are studied and the existence of intensity independent pure color patterns is demonstrated. The results are compared with two baselines: gray-scale texture analysis and color histogram analysis. The novel features improve the classification results up to 20\% and 32\% for the first and second baseline, respectively.}, language = {en} } @misc{GraesselAxerPalmetal., author = {Gr{\"a}ßel, David and Axer, Markus and Palm, Christoph and Dammers, J{\"u}rgen and Amunts, Katrin and Pietrzyk, Uwe and Zilles, Karl}, title = {Visualization of Fiber Tracts in the Postmortem Human Brain by Means of Polarized Light}, series = {NeuroImage}, volume = {47}, journal = {NeuroImage}, number = {Suppl. 1}, doi = {10.1016/S1053-8119(09)71415-6}, pages = {142}, subject = {Gehirn}, language = {en} } @article{PalmAxerGraesseletal., author = {Palm, Christoph and Axer, Markus and Gr{\"a}ßel, David and Dammers, J{\"u}rgen and Lindemeyer, Johannes and Zilles, Karl and Pietrzyk, Uwe and Amunts, Katrin}, title = {Towards ultra-high resolution fibre tract mapping of the human brain}, series = {Frontiers in Human Neuroscience}, volume = {4}, journal = {Frontiers in Human Neuroscience}, doi = {10.3389/neuro.09.009.2010}, pages = {9}, abstract = {Polarised light imaging (PLI) utilises the birefringence of the myelin sheaths in order to visualise the orientation of nerve fibres in microtome sections of adult human post-mortem brains at ultra-high spatial resolution. The preparation of post-mortem brains for PLI involves fixation, freezing and cutting into 100-μm-thick sections. Hence, geometrical distortions of histological sections are inevitable and have to be removed for 3D reconstruction and subsequent fibre tracking. We here present a processing pipeline for 3D reconstruction of these sections using PLI derived multimodal images of post-mortem brains. Blockface images of the brains were obtained during cutting; they serve as reference data for alignment and elimination of distortion artefacts. In addition to the spatial image transformation, fibre orientation vectors were reoriented using the transformation fields, which consider both affine and subsequent non-linear registration. The application of this registration and reorientation approach results in a smooth fibre vector field, which reflects brain morphology. PLI combined with 3D reconstruction and fibre tracking is a powerful tool for human brain mapping. It can also serve as an independent method for evaluating in vivo fibre tractography.}, subject = {Bildgebendes Verfahren}, language = {en} } @article{BeckerMatuschPalmetal., author = {Becker, Johanna Sabine and Matusch, Andreas and Palm, Christoph and Salber, Dagmar and Morton, Kathryn A. and Becker, Julia Susanne}, title = {Bioimaging of metals in brain tissue by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and metallomics}, series = {Metallomics}, journal = {Metallomics}, number = {2}, publisher = {Oxford Academic Press}, doi = {10.1039/b916722f}, pages = {104 -- 111}, abstract = {Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been developed and established as an emerging technique in the generation of quantitative images of metal distributions in thin tissue sections of brain samples (such as human, rat and mouse brain), with applications in research related to neurodegenerative disorders. A new analytical protocol is described which includes sample preparation by cryo-cutting of thin tissue sections and matrix-matched laboratory standards, mass spectrometric measurements, data acquisition, and quantitative analysis. Specific examples of the bioimaging of metal distributions in normal rodent brains are provided. Differences to the normal were assessed in a Parkinson's disease and a stroke brain model. Furthermore, changes during normal aging were studied. Powerful analytical techniques are also required for the determination and characterization of metal-containing proteins within a large pool of proteins, e.g., after denaturing or non-denaturing electrophoretic separation of proteins in one-dimensional and two-dimensional gels. LA-ICP-MS can be employed to detect metalloproteins in protein bands or spots separated after gel electrophoresis. MALDI-MS can then be used to identify specific metal-containing proteins in these bands or spots. The combination of these techniques is described in the second section.}, subject = {ICP-Massenspektrometrie}, language = {en} } @article{DammersAxerGraesseletal., author = {Dammers, J{\"u}rgen and Axer, Markus and Gr{\"a}ßel, David and Palm, Christoph and Zilles, Karl and Amunts, Katrin and Pietrzyk, Uwe}, title = {Signal enhancement in polarized light imaging by means of independent component analysis}, series = {NeuroImage}, volume = {49}, journal = {NeuroImage}, number = {2}, publisher = {Elsevier}, doi = {10.1016/j.neuroimage.2009.08.059}, pages = {1241 -- 1248}, abstract = {Polarized light imaging (PLI) enables the evaluation of fiber orientations in histological sections of human postmortem brains, with ultra-high spatial resolution. PLI is based on the birefringent properties of the myelin sheath of nerve fibers. As a result, the polarization state of light propagating through a rotating polarimeter is changed in such a way that the detected signal at each measurement unit of a charged-coupled device (CCD) camera describes a sinusoidal signal. Vectors of the fiber orientation defined by inclination and direction angles can then directly be derived from the optical signals employing PLI analysis. However, noise, light scatter and filter inhomogeneities interfere with the original sinusoidal PLI signals. We here introduce a novel method using independent component analysis (ICA) to decompose the PLI images into statistically independent component maps. After decomposition, gray and white matter structures can clearly be distinguished from noise and other artifacts. The signal enhancement after artifact rejection is quantitatively evaluated in 134 histological whole brain sections. Thus, the primary sinusoidal signals from polarized light imaging can be effectively restored after noise and artifact rejection utilizing ICA. Our method therefore contributes to the analysis of nerve fiber orientation in the human brain within a micrometer scale.}, subject = {Bildgebendes Verfahren}, language = {en} } @article{AxerAmuntsGraesseletal., author = {Axer, Markus and Amunts, Katrin and Gr{\"a}ßel, David and Palm, Christoph and Dammers, J{\"u}rgen and Axer, Hubertus and Pietrzyk, Uwe and Zilles, Karl}, title = {Novel Approach to the Human Connectome}, series = {NeuroImage}, volume = {54}, journal = {NeuroImage}, number = {2}, doi = {10.1016/j.neuroimage.2010.08.075}, pages = {1091 -- 1101}, abstract = {Signal transmission between different brain regions requires connecting fiber tracts, the structural basis of the human connectome. In contrast to animal brains, where a multitude of tract tracing methods can be used, magnetic resonance (MR)-based diffusion imaging is presently the only promising approach to study fiber tracts between specific human brain regions. However, this procedure has various inherent restrictions caused by its relatively low spatial resolution. Here, we introduce 3D-polarized light imaging (3D-PLI) to map the three-dimensional course of fiber tracts in the human brain with a resolution at a submillimeter scale based on a voxel size of 100 μm isotropic or less. 3D-PLI demonstrates nerve fibers by utilizing their intrinsic birefringence of myelin sheaths surrounding axons. This optical method enables the demonstration of 3D fiber orientations in serial microtome sections of entire human brains. Examples for the feasibility of this novel approach are given here. 3D-PLI enables the study of brain regions of intense fiber crossing in unprecedented detail, and provides an independent evaluation of fiber tracts derived from diffusion imaging data.}, subject = {Bildgebendes Verfahren}, language = {en} } @article{OsterholtSalberMatuschetal., author = {Osterholt, Tobias and Salber, Dagmar and Matusch, Andreas and Becker, Johanna Sabine and Palm, Christoph}, title = {IMAGENA: Image Generation and Analysis}, series = {International Journal of Mass Spectrometry}, volume = {307}, journal = {International Journal of Mass Spectrometry}, number = {1-3}, doi = {10.1016/j.ijms.2011.03.010}, pages = {232 -- 239}, abstract = {Metals are involved in many processes of life. They are needed for enzymatic reactions, are involved in healthy processes but also yield diseases if the metal homeostasis is disordered. Therefore, the interest to assess the spatial distribution of metals is rising in biomedical science. Imaging metal (and non-metal) isotopes by laser ablation mass spectrometry with inductively coupled plasma (LA-ICP-MS) requires a special software solution to process raw data obtained by scanning a sample line-by-line. As no software ready to use was available we developed an interactive software tool for Image Generation and Analysis (IMAGENA). Unless optimised for LA-ICP-MS, IMAGENA can handle other raw data as well. The general purpose was to reconstruct images from a continuous list of raw data points, to visualise these images, and to convert them into a commonly readable image file format that can be further analysed by standard image analysis software. The generation of the image starts with loading a text file that holds a data column of every measured isotope. Specifying general spatial domain settings like the data offset and the image dimensions is done by the user getting a direct feedback by means of a preview image. IMAGENA provides tools for calibration and to correct for a signal drift in the y-direction. Images are visualised in greyscale as well a pseudo-colours with possibilities for contrast enhancement. Image analysis is performed in terms of smoothed line plots in row and column direction.}, subject = {ICP-Massenspektrometrie}, language = {en} } @article{BeckerMatuschBeckeretal., author = {Becker, Johanna Sabine and Matusch, Andreas and Becker, Julia Susanne and Wu, Bei and Palm, Christoph and Becker, Albert Johann and Salber, Dagmar}, title = {Mass spectrometric imaging (MSI) of metals using advanced BrainMet techniques for biomedical research}, series = {International Journal of Mass Spectrometry}, volume = {307}, journal = {International Journal of Mass Spectrometry}, number = {1-3}, publisher = {eLSEVIER}, address = {Elsevier}, doi = {10.1016/j.ijms.2011.01.015}, pages = {3 -- 15}, abstract = {Mass spectrometric imaging (MSI) is a young innovative analytical technique and combines different fields of advanced mass spectrometry and biomedical research with the aim to provide maps of elements and molecules, complexes or fragments. Especially essential metals such as zinc, copper, iron and manganese play a functional role in signaling, metabolism and homeostasis of the cell. Due to the high degree of spatial organization of metals in biological systems their distribution analysis is of key interest in life sciences. We have developed analytical techniques termed BrainMet using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) imaging to measure the distribution of trace metals in biological tissues for biomedical research and feasibility studies—including bioaccumulation and bioavailability studies, ecological risk assessment and toxicity studies in humans and other organisms. The analytical BrainMet techniques provide quantitative images of metal distributions in brain tissue slices which can be combined with other imaging modalities such as photomicrography of native or processed tissue (histochemistry, immunostaining) and autoradiography or with in vivo techniques such as positron emission tomography or magnetic resonance tomography. Prospective and instrumental developments will be discussed concerning the development of the metalloprotein microscopy using a laser microdissection (LMD) apparatus for specific sample introduction into an inductively coupled plasma mass spectrometer (LMD-ICP-MS) or an application of the near field effect in LA-ICP-MS (NF-LA-ICP-MS). These nano-scale mass spectrometric techniques provide improved spatial resolution down to the single cell level.}, subject = {Massenspektrometrie}, language = {en} } @article{KolevKirchgessnerHoubenetal., author = {Kolev, Kalin and Kirchgeßner, Norbert and Houben, Sebastian and Csisz{\´a}r, Agnes and Rubner, Wolfgang and Palm, Christoph and Eiben, Bj{\"o}rn and Merkel, Rudolf and Cremers, Daniel}, title = {A variational approach to vesicle membrane reconstruction from fluorescence imaging}, series = {Pattern Recognition}, volume = {44}, journal = {Pattern Recognition}, number = {12}, publisher = {Elsevier}, doi = {10.1016/j.patcog.2011.04.019}, pages = {2944 -- 2958}, abstract = {Biological applications like vesicle membrane analysis involve the precise segmentation of 3D structures in noisy volumetric data, obtained by techniques like magnetic resonance imaging (MRI) or laser scanning microscopy (LSM). Dealing with such data is a challenging task and requires robust and accurate segmentation methods. In this article, we propose a novel energy model for 3D segmentation fusing various cues like regional intensity subdivision, edge alignment and orientation information. The uniqueness of the approach consists in the definition of a new anisotropic regularizer, which accounts for the unbalanced slicing of the measured volume data, and the generalization of an efficient numerical scheme for solving the arising minimization problem, based on linearization and fixed-point iteration. We show how the proposed energy model can be optimized globally by making use of recent continuous convex relaxation techniques. The accuracy and robustness of the presented approach are demonstrated by evaluating it on multiple real data sets and comparing it to alternative segmentation methods based on level sets. Although the proposed model is designed with focus on the particular application at hand, it is general enough to be applied to a variety of different segmentation tasks.}, subject = {Dreidimensionale Bildverarbeitung}, language = {en} } @article{DesernoHandelsMaierHeinetal., author = {Deserno, Thomas M. and Handels, Heinz and Maier-Hein, Klaus H. and Mersmann, Sven and Palm, Christoph and Tolxdorff, Thomas and Wagenknecht, Gudrun and Wittenberg, Thomas}, title = {Viewpoints on Medical Image Processing}, series = {Current Medical Imaging Reviews}, volume = {9}, journal = {Current Medical Imaging Reviews}, number = {2}, doi = {10.2174/1573405611309020002}, pages = {79 -- 88}, abstract = {Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment.}, subject = {Bildgebendes Verfahren}, language = {en} } @inproceedings{WeberDoenitzBrawanskietal., author = {Weber, Joachim and Doenitz, Christian and Brawanski, Alexander and Palm, Christoph}, title = {Data-Parallel MRI Brain Segmentation in Clinicial Use}, series = {Bildverarbeitung f{\"u}r die Medizin 2015; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 15. bis 17. M{\"a}rz 2015 in L{\"u}beck}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2015; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 15. bis 17. M{\"a}rz 2015 in L{\"u}beck}, publisher = {Springer}, address = {Berlin}, doi = {10.1007/978-3-662-46224-9_67}, pages = {389 -- 394}, abstract = {Structural MRI brain analysis and segmentation is a crucial part in the daily routine in neurosurgery for intervention planning. Exemplarily, the free software FSL-FAST (FMRIB's Segmentation Library - FMRIB's Automated Segmentation Tool) in version 4 is used for segmentation of brain tissue types. To speed up the segmentation procedure by parallel execution, we transferred FSL-FAST to a General Purpose Graphics Processing Unit (GPGPU) using Open Computing Language (OpenCL) [1]. The necessary steps for parallelization resulted in substantially different and less useful results. Therefore, the underlying methods were revised and adapted yielding computational overhead. Nevertheless, we achieved a speed-up factor of 3.59 from CPU to GPGPU execution, as well providing similar useful or even better results.}, subject = {Kernspintomografie}, language = {en} } @inproceedings{SzaloZehnerPalm, author = {Szalo, Alexander Eduard and Zehner, Alexander and Palm, Christoph}, title = {GraphMIC: Medizinische Bildverarbeitung in der Lehre}, series = {Bildverarbeitung f{\"u}r die Medizin 2015; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 15. bis 17. M{\"a}rz 2015 in L{\"u}beck}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2015; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 15. bis 17. M{\"a}rz 2015 in L{\"u}beck}, publisher = {Springer}, address = {Berlin}, doi = {10.1007/978-3-662-46224-9_68}, pages = {395 -- 400}, abstract = {Die Lehre der medizinischen Bildverarbeitung vermittelt Kenntnisse mit einem breiten Methodenspektrum. Neben den Grundlagen der Verfahren soll ein Gef{\"u}hl f{\"u}r eine geeignete Ausf{\"u}hrungsreihenfolge und ihrer Wirkung auf medizinische Bilddaten entwickelt werden. Die Komplexit{\"a}t der Methoden erfordert vertiefte Programmierkenntnisse, sodass bereits einfache Operationen mit großem Programmieraufwand verbunden sind. Die Software GraphMIC stellt Bildverarbeitungsoperationen in Form interaktiver Knoten zur Verf{\"u}gung und erlaubt das Arrangieren, Parametrisieren und Ausf{\"u}hren komplexer Verarbeitungssequenzen in einem Graphen. Durch den Fokus auf das Design einer Pipeline, weg von sprach- und frameworkspezifischen Implementierungsdetails, lassen sich grundlegende Prinzipien der Bildverarbeitung anschaulich erlernen. In diesem Beitrag stellen wir die visuelle Programmierung mit GraphMIC der nativen Implementierung {\"a}quivalenter Funktionen gegen{\"u}ber. Die in C++ entwickelte Applikation basiert auf Qt, ITK, OpenCV, VTK und MITK.}, subject = {Bildverarbeitung}, language = {de} } @inproceedings{WoehlHuberLoibletal., author = {W{\"o}hl, Rebecca and Huber, Michaela and Loibl, Markus and Riebschl{\"a}ger, Birgit and Nerlich, Michael and Palm, Christoph}, title = {The Impact of Semi-Automated Segmentation and 3D Analysis on Testing New Osteosynthesis Material}, series = {Bildverarbeitung f{\"u}r die Medizin 2017; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 12. bis 14. M{\"a}rz 2017 in Heidelberg}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2017; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 12. bis 14. M{\"a}rz 2017 in Heidelberg}, publisher = {Springer}, address = {Berlin}, doi = {10.1007/978-3-662-54345-0_30}, pages = {122 -- 127}, abstract = {A new protocol for testing osteosynthesis material postoperatively combining semi-automated segmentation and 3D analysis of surface meshes is proposed. By various steps of transformation and measuring, objective data can be collected. In this study the specifications of a locking plate used for mediocarpal arthrodesis of the wrist were examined. The results show, that union of the lunate, triquetrum, hamate and capitate was achieved and that the plate is comparable to coexisting arthrodesis systems. Additionally, it was shown, that the complications detected correlate to the clinical outcome. In synopsis, this protocol is considered beneficial and should be taken into account in further studies.}, subject = {Osteosynthese}, language = {en} } @inproceedings{MendelEbigboProbstetal., author = {Mendel, Robert and Ebigbo, Alanna and Probst, Andreas and Messmann, Helmut and Palm, Christoph}, title = {Barrett's Esophagus Analysis Using Convolutional Neural Networks}, series = {Bildverarbeitung f{\"u}r die Medizin 2017; Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 12. bis 14. M{\"a}rz 2017 in Heidelberg}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2017; Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 12. bis 14. M{\"a}rz 2017 in Heidelberg}, publisher = {Springer}, address = {Berlin}, doi = {10.1007/978-3-662-54345-0_23}, pages = {80 -- 85}, abstract = {We propose an automatic approach for early detection of adenocarcinoma in the esophagus. High-definition endoscopic images (50 cancer, 50 Barrett) are partitioned into a dataset containing approximately equal amounts of patches showing cancerous and non-cancerous regions. A deep convolutional neural network is adapted to the data using a transfer learning approach. The final classification of an image is determined by at least one patch, for which the probability being a cancer patch exceeds a given threshold. The model was evaluated with leave one patient out cross-validation. With sensitivity and specificity of 0.94 and 0.88, respectively, our findings improve recently published results on the same image data base considerably. Furthermore, the visualization of the class probabilities of each individual patch indicates, that our approach might be extensible to the segmentation domain.}, subject = {Speiser{\"o}hrenkrebs}, language = {en} } @inproceedings{SouzaJrHookPapaetal., author = {Souza Jr., Luis Antonio de and Hook, Christian and Papa, Jo{\~a}o Paulo and Palm, Christoph}, title = {Barrett's Esophagus Analysis Using SURF Features}, series = {Bildverarbeitung f{\"u}r die Medizin 2017; Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 12. bis 14. M{\"a}rz 2017 in Heidelberg}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2017; Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 12. bis 14. M{\"a}rz 2017 in Heidelberg}, publisher = {Springer}, address = {Berlin}, doi = {10.1007/978-3-662-54345-0_34}, pages = {141 -- 146}, abstract = {The development of adenocarcinoma in Barrett's esophagus is difficult to detect by endoscopic surveillance of patients with signs of dysplasia. Computer assisted diagnosis of endoscopic images (CAD) could therefore be most helpful in the demarcation and classification of neoplastic lesions. In this study we tested the feasibility of a CAD method based on Speeded up Robust Feature Detection (SURF). A given database containing 100 images from 39 patients served as benchmark for feature based classification models. Half of the images had previously been diagnosed by five clinical experts as being "cancerous", the other half as "non-cancerous". Cancerous image regions had been visibly delineated (masked) by the clinicians. SURF features acquired from full images as well as from masked areas were utilized for the supervised training and testing of an SVM classifier. The predictive accuracy of the developed CAD system is illustrated by sensitivity and specificity values. The results based on full image matching where 0.78 (sensitivity) and 0.82 (specificity) were achieved, while the masked region approach generated results of 0.90 and 0.95, respectively.}, subject = {Speiser{\"o}hrenkrankheit}, language = {en} } @inproceedings{FranzDreherPrinzenetal., author = {Franz, Daniela and Dreher, Maria and Prinzen, Martin and Teßmann, Matthias and Palm, Christoph and Katzky, Uwe and Perret, Jerome and Hofer, Mathias and Wittenberg, Thomas}, title = {CT-basiertes virtuelles Fr{\"a}sen am Felsenbein}, series = {Bildverarbeitung f{\"u}r die Medizin 2018; Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 11. bis 13. M{\"a}rz 2018 in Erlangen}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2018; Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 11. bis 13. M{\"a}rz 2018 in Erlangen}, publisher = {Springer}, address = {Berlin}, isbn = {978-3-662-56537-7}, doi = {10.1007/978-3-662-56537-7_51}, pages = {176 -- 181}, abstract = {Im Rahmen der Entwicklung eines haptisch-visuellen Trainingssystems f{\"u}r das Fr{\"a}sen am Felsenbein werden ein Haptikarm und ein autostereoskopischer 3D-Monitor genutzt, um Chirurgen die virtuelle Manipulation von kn{\"o}chernen Strukturen im Kontext eines sog. Serious Game zu erm{\"o}glichen. Unter anderem sollen Assistenz{\"a}rzte im Rahmen ihrer Ausbildung das Fr{\"a}sen am Felsenbein f{\"u}r das chirurgische Einsetzen eines Cochlea-Implantats {\"u}ben k{\"o}nnen. Die Visualisierung des virtuellen Fr{\"a}sens muss daf{\"u}r in Echtzeit und m{\"o}glichst realistisch modelliert, implementiert und evaluiert werden. Wir verwenden verschiedene Raycasting Methoden mit linearer und Nearest Neighbor Interpolation und vergleichen die visuelle Qualit{\"a}t und die Bildwiederholfrequenzen der Methoden. Alle verglichenen Verfahren sind sind echtzeitf{\"a}hig, unterscheiden sich aber in ihrer visuellen Qualit{\"a}t.}, subject = {Felsenbein}, language = {de} } @article{WoehlMaierGehmertetal., author = {W{\"o}hl, Rebecca and Maier, Johannes and Gehmert, Sebastian and Palm, Christoph and Riebschl{\"a}ger, Birgit and Nerlich, Michael and Huber, Michaela}, title = {3D Analysis of Osteosyntheses Material using semi-automated CT Segmentation}, series = {BMC Musculoskeletal Disorders}, volume = {19}, journal = {BMC Musculoskeletal Disorders}, publisher = {Springer Nature}, doi = {10.1186/s12891-018-1975-0}, pages = {1 -- 8}, abstract = {Backround Scaphoidectomy and midcarpal fusion can be performed using traditional fixation methods like K-wires, staples, screws or different dorsal (non)locking arthrodesis systems. The aim of this study is to test the Aptus four corner locking plate and to compare the clinical findings to the data revealed by CT scans and semi-automated segmentation. Methods: This is a retrospective review of eleven patients suffering from scapholunate advanced collapse (SLAC) or scaphoid non-union advanced collapse (SNAC) wrist, who received a four corner fusion between August 2011 and July 2014. The clinical evaluation consisted of measuring the range of motion (ROM), strength and pain on a visual analogue scale (VAS). Additionally, the Disabilities of the Arm, Shoulder and Hand (QuickDASH) and the Mayo Wrist Score were assessed. A computerized tomography (CT) of the wrist was obtained six weeks postoperatively. After semi-automated segmentation of the CT scans, the models were post processed and surveyed. Results During the six-month follow-up mean range of motion (ROM) of the operated wrist was 60°, consisting of 30° extension and 30° flexion. While pain levels decreased significantly, 54\% of grip strength and 89\% of pinch strength were preserved compared to the contralateral healthy wrist. Union could be detected in all CT scans of the wrist. While X-ray pictures obtained postoperatively revealed no pathology, two user related technical complications were found through the 3D analysis, which correlated to the clinical outcome. Conclusion Due to semi-automated segmentation and 3D analysis it has been proved that the plate design can keep up to the manufacturers' promises. Over all, this case series confirmed that the plate can compete with the coexisting techniques concerning clinical outcome, union and complication rate.}, subject = {Handchirurgie}, language = {en} } @inproceedings{MaierHuberKatzkyetal., author = {Maier, Johannes and Huber, Michaela and Katzky, Uwe and Perret, Jerome and Wittenberg, Thomas and Palm, Christoph}, title = {Force-Feedback-assisted Bone Drilling Simulation Based on CT Data}, series = {Bildverarbeitung f{\"u}r die Medizin 2018; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 11. bis 13. M{\"a}rz 2018 in Erlangen}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2018; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 11. bis 13. M{\"a}rz 2018 in Erlangen}, publisher = {Springer}, address = {Berlin}, doi = {10.1007/978-3-662-56537-7_78}, pages = {291 -- 296}, abstract = {In order to fix a fracture using minimally invasive surgery approaches, surgeons are drilling complex and tiny bones with a 2 dimensional X-ray as single imaging modality in the operating room. Our novel haptic force-feedback and visual assisted training system will potentially help hand surgeons to learn the drilling procedure in a realistic visual environment. Within the simulation, the collision detection as well as the interaction between virtual drill, bone voxels and surfaces are important. In this work, the chai3d collision detection and force calculation algorithms are combined with a physics engine to simulate the bone drilling process. The chosen Bullet-Physics-Engine provides a stable simulation of rigid bodies, if the collision model of the drill and the tool holder is generated as a compound shape. Three haptic points are added to the K-wire tip for removing single voxels from the bone. For the drilling process three modes are proposed to emulate the different phases of drilling in restricting the movement of a haptic device.}, subject = {Handchirurgie}, language = {en} } @article{GrassmannMengelkampBrandletal., author = {Graßmann, Felix and Mengelkamp, Judith and Brandl, Caroline and Harsch, Sebastian and Zimmermann, Martina E. and Linkohr, Birgit and Peters, Annette and Heid, Iris M. and Palm, Christoph and Weber, Bernhard H. F.}, title = {A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography}, series = {Ophtalmology}, volume = {125}, journal = {Ophtalmology}, number = {9}, publisher = {Elsevier}, doi = {10.1016/j.ophtha.2018.02.037}, pages = {1410 -- 1420}, abstract = {Purpose Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these require in-depth and time-consuming analysis of fundus images. Herein, we present an automated computer-based classification algorithm. Design Algorithm development for AMD classification based on a large collection of color fundus images. Validation is performed on a cross-sectional, population-based study. Participants. We included 120 656 manually graded color fundus images from 3654 Age-Related Eye Disease Study (AREDS) participants. AREDS participants were >55 years of age, and non-AMD sight-threatening diseases were excluded at recruitment. In addition, performance of our algorithm was evaluated in 5555 fundus images from the population-based Kooperative Gesundheitsforschung in der Region Augsburg (KORA; Cooperative Health Research in the Region of Augsburg) study. Methods. We defined 13 classes (9 AREDS steps, 3 late AMD stages, and 1 for ungradable images) and trained several convolution deep learning architectures. An ensemble of network architectures improved prediction accuracy. An independent dataset was used to evaluate the performance of our algorithm in a population-based study. Main Outcome Measures. κ Statistics and accuracy to evaluate the concordance between predicted and expert human grader classification. Results. A network ensemble of 6 different neural net architectures predicted the 13 classes in the AREDS test set with a quadratic weighted κ of 92\% (95\% confidence interval, 89\%-92\%) and an overall accuracy of 63.3\%. In the independent KORA dataset, images wrongly classified as AMD were mainly the result of a macular reflex observed in young individuals. By restricting the KORA analysis to individuals >55 years of age and prior exclusion of other retinopathies, the weighted and unweighted κ increased to 50\% and 63\%, respectively. Importantly, the algorithm detected 84.2\% of all fundus images with definite signs of early or late AMD. Overall, 94.3\% of healthy fundus images were classified correctly. Conclusions Our deep learning algoritm revealed a weighted κ outperforming human graders in the AREDS study and is suitable to classify AMD fundus images in other datasets using individuals >55 years of age.}, subject = {Senile Makuladegeneration}, language = {en} }