@article{BeckerZoriyMatuschetal., author = {Becker, Johanna Sabine and Zoriy, Miroslav and Matusch, Andreas and Wu, Bei and Salber, Dagmar and Palm, Christoph and Becker, Julia Susanne}, title = {Bioimaging of Metals by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS)}, series = {Mass Spectrometry Reviews}, volume = {29}, journal = {Mass Spectrometry Reviews}, doi = {10.1002/mas.20239}, pages = {156 -- 175}, abstract = {The distribution analysis of (essential, beneficial, or toxic) metals (e.g., Cu, Fe, Zn, Pb, and others), metalloids, and non-metals in biological tissues is of key interest in life science. Over the past few years, the development and application of several imaging mass spectrometric techniques has been rapidly growing in biology and medicine. Especially, in brain research metalloproteins are in the focus of targeted therapy approaches of neurodegenerative diseases such as Alzheimer's and Parkinson's disease, or stroke, or tumor growth. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) using double-focusing sector field (LA-ICP-SFMS) or quadrupole-based mass spectrometers (LA-ICP-QMS) has been successfully applied as a powerful imaging (mapping) technique to produce quantitative images of detailed regionally specific element distributions in thin tissue sections of human or rodent brain. Imaging LA-ICP-QMS was also applied to investigate metal distributions in plant and animal sections to study, for example, the uptake and transport of nutrient and toxic elements or environmental contamination. The combination of imaging LA-ICP-MS of metals with proteomic studies using biomolecular mass spectrometry identifies metal-containing proteins and also phosphoproteins. Metal-containing proteins were imaged in a two-dimensional gel after electrophoretic separation of proteins (SDS or Blue Native PAGE). Recent progress in LA-ICP-MS imaging as a stand-alone technique and in combination with MALDI/ESI-MS for selected life science applications is summarized.}, subject = {Bildgebendes Verfahren}, language = {en} } @article{IlgnerPalmSchuetzetal., author = {Ilgner, Justus F. R. and Palm, Christoph and Sch{\"u}tz, Andreas G. and Spitzer, Klaus and Westhofen, Martin and Lehmann, Thomas M.}, title = {Colour Texture Analysis for Quantitative Laryngoscopy}, series = {Acta Otolaryngologica}, volume = {123}, journal = {Acta Otolaryngologica}, doi = {10.1080/00016480310000412}, pages = {730 -- 734}, abstract = {Whilst considerable progress has been made in enhancing the quality of indirect laryngoscopy and image processing, the evaluation of clinical findings is still based on the clinician's judgement. The aim of this paper was to examine the feasibility of an objective computer-based method for evaluating laryngeal disease. Digitally recorded images obtained by 90 degree- and 70 degree-angled indirect rod laryngoscopy using standardized white balance values were made of 16 patients and 19 healthy subjects. The digital images were evaluated manually by the clinician based on a standardized questionnaire, and suspect lesions were marked and classified on the image. Following colour separation, normal vocal cord areas as well as suspect lesions were analyzed automatically using co-occurrence matrices, which compare colour differences between neighbouring pixels over a predefined distance. Whilst colour histograms did not provide sufficient information for distinguishing between healthy and diseased tissues, consideration of the blue content of neighbouring pixels enabled a correct classification in 81.4\% of cases. If all colour channels (red, green and blue) were regarded simultaneously, the best classification correctness obtained was 77.1\%. Although only a very basic classification differentiating between healthy and diseased tissue was attempted, the results showed progress compared to grey-scale histograms, which have been evaluated before. The results document a first step towards an objective, machine-based classification of laryngeal images, which could provide the basis for further development of an expert system for use in indirect laryngoscopy.}, language = {en} } @article{PalmVietenSalberetal., author = {Palm, Christoph and Vieten, Andrea and Salber, Dagmar and Pietrzyk, Uwe}, title = {Evaluation of Registration Strategies for Multi-modality Images of Rat Brain Slices}, series = {Physics in Medicine and Biology}, volume = {54}, journal = {Physics in Medicine and Biology}, number = {10}, doi = {10.1088/0031-9155/54/10/021}, pages = {3269 -- 3289}, abstract = {In neuroscience, small-animal studies frequently involve dealing with series of images from multiple modalities such as histology and autoradiography. The consistent and bias-free restacking of multi-modality image series is obligatory as a starting point for subsequent non-rigid registration procedures and for quantitative comparisons with positron emission tomography (PET) and other in vivo data. Up to now, consistency between 2D slices without cross validation using an inherent 3D modality is frequently presumed to be close to the true morphology due to the smooth appearance of the contours of anatomical structures. However, in multi-modality stacks consistency is difficult to assess. In this work, consistency is defined in terms of smoothness of neighboring slices within a single modality and between different modalities. Registration bias denotes the distortion of the registered stack in comparison to the true 3D morphology and shape. Based on these metrics, different restacking strategies of multi-modality rat brain slices are experimentally evaluated. Experiments based on MRI-simulated and real dual-tracer autoradiograms reveal a clear bias of the restacked volume despite quantitatively high consistency and qualitatively smooth brain structures. However, different registration strategies yield different inter-consistency metrics. If no genuine 3D modality is available, the use of the so-called SOP (slice-order preferred) or MOSOP (modality-and-slice-order preferred) strategy is recommended.}, subject = {Histologie}, 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} } @inproceedings{EibenPalmPietrzyketal., author = {Eiben, Bj{\"o}rn and Palm, Christoph and Pietrzyk, Uwe and Davatzikos, Christos and Amunts, Katrin}, title = {Error Correction using Registration for Blockface Volume Reconstruction of Serial Histological Sections of the Human Brain}, series = {Bildverarbeitung f{\"u}r die Medizin 2010; Algorithmen - Systeme - Anwendungen ; Proceedings des Workshops vom 22. bis 25. M{\"a}rz 2009 in Heidelberg}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2010; Algorithmen - Systeme - Anwendungen ; Proceedings des Workshops vom 22. bis 25. M{\"a}rz 2009 in Heidelberg}, publisher = {Springer}, address = {Berlin}, pages = {301 -- 305}, abstract = {For accurate registration of histological sections blockface images are frequently used as three dimensional reference. However, due to the use of endocentric lenses the images suffer from perspective errors such as scaling and seemingly relative movement of planes which are located in different distances parallel to the imaging sensor. The suggested correction of those errors is based on the estimation of scaling factors derived from image registration of regions characterized by differing distances to the point of view in neighboring sections. The correction allows the generation of a consistent three dimensional blockface volume.}, subject = {Histologie}, language = {en} } @misc{BeyerWeigertPalmetal., author = {Beyer, Thomas and Weigert, Markus and Palm, Christoph and Quick, Harald H. and M{\"u}ller, Stefan P. and Pietrzyk, Uwe and Vogt, Florian and Martinez, M.J. and Bockisch, Andreas}, title = {Towards MR-based attenuation correction for whole-body PET/MR imaging}, series = {The Journal of Nuclear Medicine}, volume = {47}, journal = {The Journal of Nuclear Medicine}, number = {Suppl. 1}, pages = {384P}, subject = {Kernspintomografie}, 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} } @misc{WeigertBeyerQuicketal., author = {Weigert, Markus and Beyer, Thomas and Quick, Harald H. and Pietrzyk, Uwe and Palm, Christoph and M{\"u}ller, Stefan P.}, title = {Generation of a MRI reference data set for the validation of automatic, non-rigid image co-registration algorithms}, series = {Nuklearmedizin}, volume = {46}, journal = {Nuklearmedizin}, number = {2}, pages = {A116}, subject = {Kernspintomografie}, language = {en} } @article{SouzaJrMendelStrasseretal., author = {Souza Jr., Luis Antonio de and Mendel, Robert and Strasser, Sophia and Ebigbo, Alanna and Probst, Andreas and Messmann, Helmut and Papa, Jo{\~a}o Paulo and Palm, Christoph}, title = {Convolutional Neural Networks for the evaluation of cancer in Barrett's esophagus: Explainable AI to lighten up the black-box}, series = {Computers in Biology and Medicine}, volume = {135}, journal = {Computers in Biology and Medicine}, publisher = {Elsevier}, issn = {0010-4825}, doi = {10.1016/j.compbiomed.2021.104578}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-20126}, pages = {1 -- 14}, abstract = {Even though artificial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their level of accountability and transparency must be provided in such evaluations. The reliability related to machine learning predictions must be explained and interpreted, especially if diagnosis support is addressed. For this task, the black-box nature of deep learning techniques must be lightened up to transfer its promising results into clinical practice. Hence, we aim to investigate the use of explainable artificial intelligence techniques to quantitatively highlight discriminative regions during the classification of earlycancerous tissues in Barrett's esophagus-diagnosed patients. Four Convolutional Neural Network models (AlexNet, SqueezeNet, ResNet50, and VGG16) were analyzed using five different interpretation techniques (saliency, guided backpropagation, integrated gradients, input × gradients, and DeepLIFT) to compare their agreement with experts' previous annotations of cancerous tissue. We could show that saliency attributes match best with the manual experts' delineations. Moreover, there is moderate to high correlation between the sensitivity of a model and the human-and-computer agreement. The results also lightened that the higher the model's sensitivity, the stronger the correlation of human and computational segmentation agreement. We observed a relevant relation between computational learning and experts' insights, demonstrating how human knowledge may influence the correct computational learning.}, subject = {Deep Learning}, language = {en} } @inproceedings{PietrzykBauerVietenetal., author = {Pietrzyk, Uwe and Bauer, Dagmar and Vieten, Andrea and Bauer, Andreas and Langen, Karl-Josef and Zilles, Karl and Palm, Christoph}, title = {Creating consistent 3D multi-modality data sets from autoradiographic and histological images of the rat brain}, series = {IEEE Nuclear Science Symposium Conference Record}, volume = {6}, booktitle = {IEEE Nuclear Science Symposium Conference Record}, doi = {10.1109/NSSMIC.2004.1466754}, pages = {4001 -- 4003}, abstract = {Volumetric representations of autoradiographic and histological images gain ever more interest as a base to interpret data obtained with /spl mu/-imaging devices like microPET. Beyond supporting spatial orientation within rat brains especially autoradiographic images may serve as a base to quantitatively evaluate the complex uptake patterns of microPET studies with receptor ligands or tumor tracers. They may also serve for the development of rat brain atlases or data models, which can be explored during further image analysis or simulation studies. In all cases a consistent spatial representation of the rat brain, i.e. its anatomy and the corresponding quantitative uptake pattern, is required. This includes both, a restacking of the individual two-dimensional images and the exact registration of the respective volumes. We propose strategies how these volumes can be created in a consistent way and trying to limit the requirements on the circumstances during data acquisition, i.e. being independent from other sources like video imaging of the block face prior to cutting or high resolution micro-X-ray CT or micro MRI.}, language = {en} } @article{BauerHamacherBroeeretal., author = {Bauer, Dagmar and Hamacher, Kurt and Br{\"o}er, Stefan and Pauleit, Dirk and Palm, Christoph and Zilles, Karl and Coenen, Heinz H. and Langen, Karl-Josef}, title = {Preferred stereoselective brain uptake of D-serine}, series = {Nuclear Medicine and Biology}, volume = {32}, journal = {Nuclear Medicine and Biology}, number = {8}, doi = {10.1016/j.nucmedbio.2005.07.004}, pages = {793 -- 797}, abstract = {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.}, subject = {Aminos{\"a}uren}, language = {en} } @article{LehmannPalm, author = {Lehmann, Thomas M. and Palm, Christoph}, title = {Color Line Search for Illuminant Estimation in Real World Scenes}, series = {Journal of the Optical Society of America (JOSA) A}, volume = {18}, journal = {Journal of the Optical Society of America (JOSA) A}, number = {11}, doi = {10.1364/JOSAA.18.002679}, pages = {2679 -- 2691}, abstract = {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.}, language = {en} } @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} }