TY - JOUR A1 - Bauer, Dagmar A1 - Hamacher, Kurt A1 - Bröer, Stefan A1 - Pauleit, Dirk A1 - Palm, Christoph A1 - Zilles, Karl A1 - Coenen, Heinz H. A1 - Langen, Karl-Josef T1 - Preferred stereoselective brain uptake of D-serine BT - a modulator of glutamatergic neurotransmission JF - Nuclear Medicine and Biology N2 - Although it has long been presumed that d-amino acids are uncommon in mammalians, substantial amounts of free d-serine have been detected in the mammalian brain. d-Serine has been demonstrated to be an important modulator of glutamatergic neurotransmission and acts as an agonist at the strychnine-insensitive glycine site of N-methyl-d-aspartate receptors. The blood-to-brain transfer of d-serine is thought to be extremely low, and it is assumed that d-serine is generated by isomerization of l-serine in the brain. Stimulated by the observation of a preferred transport of the d-isomer of proline at the blood–brain barrier, we investigated the differential uptake of [3H]-d-serine and [3H]-l-serine in the rat brain 1 h after intravenous injection using quantitative autoradiography. Surprisingly, brain uptake of [3H]-d-serine was significantly higher than that of [3H]-l-serine, indicating a preferred transport of the d-enantiomer of serine at the blood–brain barrier. This finding indicates that exogenous d-serine may have a direct influence on glutamatergic neurotransmission and associated diseases. KW - Aminosäuren KW - Gehirn KW - Blut-Hirn-Schranke KW - Aufnahme KW - d/l-serine KW - Amino acid transport KW - Blood–brain barrier KW - NMDA receptors Y1 - 2005 U6 - https://doi.org/10.1016/j.nucmedbio.2005.07.004 VL - 32 IS - 8 SP - 793 EP - 797 ER - TY - JOUR A1 - Lehmann, Thomas M. A1 - Palm, Christoph T1 - Color Line Search for Illuminant Estimation in Real World Scenes JF - Journal of the Optical Society of America (JOSA) A N2 - The estimation of illuminant color is mandatory for many applications in the field of color image quantification. However, it is an unresolved problem if no additional heuristics or restrictive assumptions apply. Assuming uniformly colored and roundly shaped objects, Lee has presented a theory and a method for computing the scene-illuminant chromaticity from specular highlights [H. C. Lee, J. Opt. Soc. Am. A 3, 1694 (1986)]. However, Lee’s method, called image path search, is less robust to noise and is limited in the handling of microtextured surfaces. We introduce a novel approach to estimate the color of a single illuminant for noisy and microtextured images, which frequently occur in real-world scenes. Using dichromatic regions of different colored surfaces, our approach, named color line search, reverses Lee’s strategy of image path search. Reliable color lines are determined directly in the domain of the color diagrams by three steps. First, regions of interest are automatically detected around specular highlights, and local color diagrams are computed. Second, color lines are determined according to the dichromatic reflection model by Hough transform of the color diagrams. Third, a consistency check is applied by a corresponding path search in the image domain. Our method is evaluated on 40 natural images of fruit and vegetables. In comparison with those of Lee’s method, accuracy and stability are substantially improved. In addition, the color line search approach can easily be extended to scenes of objects with macrotextured surfaces. Y1 - 2001 U6 - https://doi.org/10.1364/JOSAA.18.002679 VL - 18 IS - 11 SP - 2679 EP - 2691 ER - TY - JOUR A1 - Palm, Christoph T1 - Color Texture Classification by Integrative Co-Occurrence Matrices JF - Pattern Recognition N2 - 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. KW - Color texture KW - Co-occurrence matrix KW - Integrative features KW - KolmogKorov distance KW - Image classification Y1 - 2004 U6 - https://doi.org/10.1016/j.patcog.2003.09.010 VL - 37 IS - 5 SP - 965 EP - 976 ER - TY - CHAP A1 - Palm, Christoph A1 - Vieten, Andrea A1 - Bauer, Dagmar A1 - Pietrzyk, Uwe T1 - Evaluierung von Registrierungsstrategien zur multimodalen 3D-Rekonstruktion von Rattenhirnschnitten T2 - Bildverarbeitung für die Medizin 2006 N2 - In dieser Arbeit werden drei Strategien zur 3D Stapelung von multimodalen Schnittbildern vorgestellt. Die Strategien werden experimentell anhand von Dualtracer-Autoradiographien evaluiert. Dazu werden neue Maße zur Beschreibung der Konsistenz innerhalb einer Modalität und der Konsistenz der Modalitäten untereinander entwickelt, die auf bekannten Registrierungsmetriken basieren. Gerade bezüglich der Konsistenz der Modalitäten untereinander zeigen zwei Strategien die besten Resultate: (1) abwechselnde multimodale Registrierung (2) monomodale Rekonstruktion einer Modalität und multimodale 2D Registrierung der zweiten Modalität. KW - Registrierung KW - Dreidimensionale Rekonstruktion KW - Gehirn KW - Schnittpräparat Y1 - 2006 U6 - https://doi.org/10.1007/3-540-32137-3_51 SP - 251 EP - 255 PB - Springer CY - Berlin ER - TY - CHAP A1 - Pietrzyk, Uwe A1 - Palm, Christoph A1 - Beyer, Thomas T1 - Fusion strategies in multi-modality imaging T2 - Medical Physics, Vol 2. Proceedings of the jointly held Congresses: ICMP 2005, 14th International Conference of Medical Physics of the International Organization for Medical Physics (IOMP), the European Federation of Organizations in Medical Physics (EFOMP) and the German Society of Medical Physics (DGMP) ; BMT 2005, 39th Annual Congress of the German Society for Biomedical Engineering (DGBMT) within VDE ; 14th - 17th September 2005, Nuremberg, Germany KW - Bildgebendes Verfahren KW - Registrierung Y1 - 2005 SP - 1446 EP - 1447 ER - TY - GEN A1 - Weigert, Markus A1 - Palm, Christoph A1 - Quick, Harald H. A1 - Müller, Stefan P. A1 - Pietrzyk, Uwe A1 - Beyer, Thomas T1 - Template for MR-based attenuation correction for whole-body PET/MR imaging T2 - Nuklearmedizin KW - Kernspintomografie KW - Positronen-Emissions-Tomografie KW - Bildgebendes Verfahren KW - Schwächung Y1 - 2007 VL - 46 IS - 2 SP - A115 ER - TY - GEN A1 - Axer, Markus A1 - Axer, Hubertus A1 - Palm, Christoph A1 - Gräßel, David A1 - Zilles, Karl A1 - Pietrzyk, Uwe T1 - Visualization of Nerve Fibre Orientation in the Visual Cortex of the Human Brain by Means of Polarized Light T2 - Biomedizinische Technik KW - Sehrinde KW - Nervenfaser KW - Ausrichtung KW - Visualisierung KW - Polarisiertes Licht Y1 - 2007 VL - 52 IS - Suppl. SP - 1569048-041 ER - TY - CHAP A1 - Palm, Christoph A1 - Dehnhardt, Markus A1 - Vieten, Andrea A1 - Pietrzyk, Uwe T1 - 3D rat brain tumor reconstruction T2 - Biomedizinische Technik KW - Dreidimensionale Rekonstruktion KW - Hirntumor Y1 - 2005 VL - 50 IS - Suppl. 1, Part 1 SP - 597 EP - 598 ER - TY - GEN A1 - Palm, Christoph A1 - Crum, William R. A1 - Pietrzyk, Uwe A1 - Hawkes, David J. T1 - Application of Fluid and Elastic Registration Methods to Histological Rat Brain Sections T2 - Biomedizinische Technik KW - Registrierung KW - Gehirn KW - Schnittdarstellung Y1 - 2007 VL - 52 IS - Suppl. ER - TY - JOUR A1 - Brown, Peter A1 - Consortium, RELISH A1 - Zhou, Yaoqi A1 - Palm, Christoph T1 - Large expert-curated database for benchmarking document similarity detection in biomedical literature search JF - Database N2 - Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research. KW - Information Retrieval KW - Indexierung KW - Literaturdatenbank KW - Dokument KW - Ähnlichkeitssuche KW - Suchmaschine Y1 - 2019 U6 - https://doi.org/10.1093/database/baz085 VL - 2019 SP - 1 EP - 66 PB - Oxford University Pres ER - TY - GEN A1 - Ebigbo, Alanna A1 - Mendel, Robert A1 - Probst, Andreas A1 - Manzeneder, Johannes A1 - Souza Jr., Luis Antonio de A1 - Papa, João Paulo A1 - Palm, Christoph A1 - Messmann, Helmut T1 - Artificial Intelligence in Early Barrett's Cancer: The Segmentation Task T2 - Endoscopy N2 - Aims: The delineation of outer margins of early Barrett's cancer can be challenging even for experienced endoscopists. Artificial intelligence (AI) could assist endoscopists faced with this task. As of date, there is very limited experience in this domain. In this study, we demonstrate the measure of overlap (Dice coefficient = D) between highly experienced Barrett endoscopists and an AI system in the delineation of cancer margins (segmentation task). Methods: An AI system with a deep convolutional neural network (CNN) was trained and tested on high-definition endoscopic images of early Barrett's cancer (n = 33) and normal Barrett's mucosa (n = 41). The reference standard for the segmentation task were the manual delineations of tumor margins by three highly experienced Barrett endoscopists. Training of the AI system included patch generation, patch augmentation and adjustment of the CNN weights. Then, the segmentation results from patch classification and thresholding of the class probabilities. Segmentation results were evaluated using the Dice coefficient (D). Results: The Dice coefficient (D) which can range between 0 (no overlap) and 1 (complete overlap) was computed only for images correctly classified by the AI-system as cancerous. At a threshold of t = 0.5, a mean value of D = 0.72 was computed. Conclusions: AI with CNN performed reasonably well in the segmentation of the tumor region in Barrett's cancer, at least when compared with expert Barrett's endoscopists. AI holds a lot of promise as a tool for better visualization of tumor margins but may need further improvement and enhancement especially in real-time settings. KW - Speiseröhrenkrankheit KW - Maschinelles Lernen KW - Barrett's esphagus KW - Deep Learning KW - Segmentation Y1 - 2019 U6 - https://doi.org/10.1055/s-0039-1681187 VL - 51 IS - 04 SP - 6 PB - Georg Thieme Verlag CY - Stuttgart ER - TY - CHAP A1 - Palm, Christoph A1 - Lehmann, Thomas M. A1 - Bredno, J. A1 - Neuschaefer-Rube, C. A1 - Klajman, S. A1 - Spitzer, Klaus T1 - Automated Analysis of Stroboscopic Image Sequences by Vibration Profiles T2 - Advances in Quantitative Laryngoscopy, Voice and Speech Research, Procs. 5th International Workshop N2 - A method for automated segmentation of vocal cords in stroboscopic video sequences is presented. In contrast to earlier approaches, the inner and outer contours of the vocal cords are independently delineated. Automatic segmentation of the low contrasted images is carried out by connecting the shape constraint of a point distribution model to a multi-channel regionbased balloon model. This enables us to robustly compute a vibration profile that is used as a new diagnostic tool to visualize several vibration parameters in only one graphic. The vibration profiles are studied in two cases: one physiological vibration and one functional pathology. KW - Vibration Profile KW - Stroboscopic Images KW - Contour Detection KW - Balloon Model KW - Point Distribution Model Y1 - 2001 UR - https://www.researchgate.net/publication/242439073_Automated_Analysis_of_Stroboscopic_Image_Sequences_by_Vibration_Profiles ER - TY - CHAP A1 - Palm, Christoph A1 - Fischer, B. A1 - Lehmann, Thomas M. A1 - Spitzer, Klaus T1 - Hierarchische Wasserscheiden-Transformation zur Lippensegmentierung in Farbbildern T2 - Bildverarbeitung für die Medizin 2000 N2 - Zur Lösung komplexer Segmentierungsprobleme wird eine hierarchische und farbbasierte Wasserscheidentransformation vorgestellt. Geringe Modifikationen bezüglich Startpunktwahl und Flutungsprozess resultieren in signifikanten Verbesserungen der Segmentierung. Das Verfahren wurde zur Lippendetektion in Farbbildsequenzen eingesetzt, die zur quantitativen Beschreibung von Sprechbewegungsabläufen automatisch ausgewertet werden. Die Experimente mit 245 Bildern aus 6 Sequenzen zeigten eine Fehlerrate von 13%. KW - Hierarchische Wasserscheiden-Transformation KW - Segmentierung der Lippen KW - Bewegungsanalyse KW - Farbbildverarbeitung Y1 - 2000 U6 - https://doi.org/10.1007/978-3-642-59757-2_20 SP - 106 EP - 110 PB - Springer CY - Berlin ER - TY - CHAP A1 - Palm, Christoph A1 - Lehmann, Thomas M. A1 - Spitzer, Klaus T1 - Color Texture Analysis of Moving Vocal Cords Using Approaches from Statistics and Signal Theory T2 - Advances in Quantitative Laryngoscopy, Voice and Speech Research, Procs. 4th International Workshop, Friedrich Schiller University, Jena N2 - Textural features are applied for detection of morphological pathologies of vocal cords. Cooccurrence matrices as statistical features are presented as well as filter bank analysis by Gabor filters. Both methods are extended to handle color images. Their robustness against camera movement and vibration of vocal cords is evaluated. Classification results due to three in vivo sequences are in between 94.4 % and 98.9%. The classification errors decrease if color features are used instead of grayscale features for both statistical and Fourier features KW - Color Texture KW - Gabor Filter KW - Cooccurrence Matrix KW - Image Processing Y1 - 2000 SP - 49 EP - 56 ER - TY - JOUR A1 - Neuschaefer-Rube, C. A1 - Lehmann, Thomas M. A1 - Palm, Christoph A1 - Bredno, J. A1 - Klajman, S. A1 - Spitzer, Klaus T1 - 3D-Visualisierung glottaler Abduktionsbewegungen JF - Aktuelle phoniatrisch-pädaudiologische Aspekte Y1 - 2001 SN - 3-922766-76-5 VL - 2001/2002 IS - 9 SP - 58 EP - 61 PB - Median ER - TY - CHAP A1 - Fischer, B. A1 - Palm, Christoph A1 - Lehmann, Thomas M. A1 - Spitzer, Klaus T1 - Selektion von Farbtexturmerkmalen zur Tumorklassifikation dermatoskopischer Fotografien T2 - Bildverarbeitung für die Medizin 2002 Y1 - 2002 SP - 238 EP - 241 PB - Springer CY - Berlin ER - TY - BOOK A1 - Palm, Christoph T1 - Integrative Auswertung von Farbe und Textur Y1 - 2003 UR - http://publications.rwth-aachen.de/record/58707/files/Palm_Christoph.pdf PB - Der Andere Verlag ER - TY - JOUR A1 - Palm, Christoph A1 - Dehnhardt, Markus A1 - Vieten, Andrea A1 - Pietrzyk, Uwe A1 - Bauer, Andreas A1 - Zilles, Karl T1 - 3D rat brain tumors JF - Naunyn-Schmiedebergs Archives of Pharmacology Y1 - 2005 VL - 371 IS - R103 ER - TY - CHAP A1 - Palm, Christoph A1 - Scholl, Ingrid A1 - Lehmann, Thomas M. A1 - Spitzer, Klaus ED - Greiser, E. ED - Wischnewsky, M. T1 - Nutzung eines Farbkonstanz-Algorithmus zur Entfernung von Glanzlichtern in laryngoskopischen Bildern T2 - Methoden der Medizinischen Informatik, Biometrie und Epidemiologie in der modernen Informationsgesellschaft N2 - 1 Einführung Funktionelle und organische Störungen im Larynx beeinträchtigen die Ausdrucksfähigkeit 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 unabhängige Aufnahme der drei Farbkanäle erlaubt. Die bisherige subjektive Befundung ist von der Erfahrung des Untersuchers abhängig und läßt nur eine grobe Klassifikation der Krankheitsbilder zu. Zur Objektivierung werden daher quantitative Parameter für 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 führen und so weite Bereiche der Stimmlippen für die Farb-und Texturanalyse unbrauchbar machen. Dieser Beitrag stellt einen Farbkonstanz-Algorithmus vor, der unabhängig von der Lichtquelle quantitative Farbwerte des Gewebes liefert und die Glanzlichtdetektion und -elimination ermöglicht. 2 Methodik Ziel des Farbkonstanz-Algorithmus ist die Trennung von Lichtquellen-und Gewebefarbe. Unter Verwendung des dichromatischen Reflexionsmodells [1] kann die Oberflächenreflexion mit der Farbe der Lichtquelle und die Körperreflexion mit der Gewebefarbe identifiziert werden. Der Farbeindruck entsteht aus der Linearkombination beider Farbkomponenten. Ihre Gewichtung ist von der Aufnahmegeometrie abhängig, insbesondere vom Winkel zwischen Oberflächennormalen und dem Positionsvektor der Lichtquelle. In einem zweistufigen Verfahren wird zunächst die Lichtquellenfarbe geschätzt, dann die Gewebefarbe ermittelt. Hieraus können beide Farbanteile durch die Berechnung der Gewichtsfaktoren pixelweise getrennt werden. KW - Farbkonstanz KW - Glanzlichtelimination KW - medizinische Bildverarbeitung KW - dichromatisches Reflexionsmodell Y1 - 1998 SN - 9783820813357 SP - 300 EP - 303 PB - MMV Medien und Medizin CY - München ER - TY - CHAP A1 - Chang, Ching-Sheng A1 - Lin, Jin-Fa A1 - Lee, Ming-Ching A1 - Palm, Christoph ED - Tolxdorff, Thomas ED - Deserno, Thomas M. ED - Handels, Heinz ED - Maier, Andreas ED - Maier-Hein, Klaus H. ED - Palm, Christoph T1 - Semantic Lung Segmentation Using Convolutional Neural Networks T2 - Bildverarbeitung für die Medizin 2020. Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin N2 - Chest X-Ray (CXR) images as part of a non-invasive diagnosis method are commonly used in today’s medical workflow. In traditional methods, physicians usually use their experience to interpret CXR images, however, there is a large interobserver variance. Computer vision may be used as a standard for assisted diagnosis. In this study, we applied an encoder-decoder neural network architecture for automatic lung region detection. We compared a three-class approach (left lung, right lung, background) and a two-class approach (lung, background). The differentiation of left and right lungs as direct result of a semantic segmentation on basis of neural nets rather than post-processing a lung-background segmentation is done here for the first time. Our evaluation was done on the NIH Chest X-ray dataset, from which 1736 images were extracted and manually annotated. We achieved 94:9% mIoU and 92% mIoU as segmentation quality measures for the two-class-model and the three-class-model, respectively. This result is very promising for the segmentation of lung regions having the simultaneous classification of left and right lung in mind. KW - Neuronales Netz KW - Segmentierung KW - Brustkorb KW - Deep Learning KW - Encoder-Decoder Network KW - Chest X-Ray Y1 - 2020 SN - 978-3-658-29266-9 U6 - https://doi.org/10.1007/978-3-658-29267-6_17 SP - 75 EP - 80 PB - Springer Vieweg CY - Wiesbaden ER -