@article{LubeFlackCotofanaetal.2017, author = {Lube, Juliane and Flack, Natasha and Cotofana, Sebastian and {\"O}zkurtul, Orkun and Woodley, Stephanie and Zachow, Stefan and Hammer, Niels}, title = {Pelvic and lower extremity physiological cross-sectional areas: An MRI study of the living young and comparison to published research literature}, volume = {39}, journal = {Surgical and Radiologic Anatomy}, number = {8}, doi = {10.1007/s00276-016-1807-6}, pages = {849 -- 857}, year = {2017}, abstract = {Purpose: Morphological data pertaining to the pelvis and lower extremity muscles are increasingly being used in biomechanical modeling to compare healthy and pathological conditions. Very few data sets exist that encompass all of the muscles of the lower limb, allowing for comparisons between regions. The aims of this study were to (a) provide physiological cross-sectional area (PCSA) data for the pelvic, thigh, and leg muscles in young, healthy participants, using magnetic resonance imaging (MRI), and (b) to compare these data with summarized PCSAs obtained from the literature. Materials and Methods: Six young and healthy volunteers participated and were scanned using 3 T MRI. PCSAs were calculated from volumetric segmentations obtained bilaterally of 28 muscles/muscle groups of the pelvis, thigh, and leg. These data were compared to published, summarized PCSA data derived from cadaveric, computed tomography, MRI and ultrasound studies. Results: The PCSA of the pelvis, thigh, and leg muscles tended to be 20-130\% larger in males than in females, except for the gemelli which were 34\% smaller in males, and semitendinosus and triceps surae which did not differ (<20\% different). The dominant and the non-dominant sides showed similar and minutely different PCSA with less than 18\% difference between sides. Comparison to other studies revealed wide ranges within, and large differences between, the cadaveric and imaging PCSA data. Comparison of the PCSA of this study and published literature revealed major differences in the iliopsoas, gluteus minimus, tensor fasciae latae, gemelli, obturator internus, biceps femoris, quadriceps femoris, and the deep leg flexor muscles. Conclusions: These volume-derived PCSAs of the pelvic and lower limb muscles alongside the data synthesised from the literature may serve as a basis for comparative and biomechanical studies of the living and healthy young, and enable calculation of muscle forces. Comparison of the literature revealed large variations in PCSA from each of the different investigative modalities, hampering omparability between studies. Sample size, age, post-mortem changes of muscle tone, chemical fixation of cadaveric tissues, and the underlying physics of the imaging techniques may potentially influence PCSA calculations.}, language = {en} } @inproceedings{MukhopadhyayMorilloZachowetal.2016, author = {Mukhopadhyay, Anirban and Morillo, Oscar and Zachow, Stefan and Lamecker, Hans}, title = {Robust and Accurate Appearance Models Based on Joint Dictionary Learning Data from the Osteoarthritis Initiative}, volume = {9993}, booktitle = {Lecture Notes in Computer Science, Patch-Based Techniques in Medical Imaging. Patch-MI 2016}, doi = {10.1007/978-3-319-47118-1_4}, pages = {25 -- 33}, year = {2016}, abstract = {Deformable model-based approaches to 3D image segmentation have been shown to be highly successful. Such methodology requires an appearance model that drives the deformation of a geometric model to the image data. Appearance models are usually either created heuristically or through supervised learning. Heuristic methods have been shown to work effectively in many applications but are hard to transfer from one application (imaging modality/anatomical structure) to another. On the contrary, supervised learning approaches can learn patterns from a collection of annotated training data. In this work, we show that the supervised joint dictionary learning technique is capable of overcoming the traditional drawbacks of the heuristic approaches. Our evaluation based on two different applications (liver/CT and knee/MR) reveals that our approach generates appearance models, which can be used effectively and efficiently in a deformable model-based segmentation framework.}, language = {en} } @article{SahuMukhopadhyaySzengeletal.2017, author = {Sahu, Manish and Mukhopadhyay, Anirban and Szengel, Angelika and Zachow, Stefan}, title = {Addressing multi-label imbalance problem of Surgical Tool Detection using CNN}, volume = {12}, journal = {International Journal of Computer Assisted Radiology and Surgery}, number = {6}, publisher = {Springer}, doi = {10.1007/s11548-017-1565-x}, pages = {1013 -- 1020}, year = {2017}, abstract = {Purpose: A fully automated surgical tool detection framework is proposed for endoscopic video streams. State-of-the-art surgical tool detection methods rely on supervised one-vs-all or multi-class classification techniques, completely ignoring the co-occurrence relationship of the tools and the associated class imbalance. Methods: In this paper, we formulate tool detection as a multi-label classification task where tool co-occurrences are treated as separate classes. In addition, imbalance on tool co-occurrences is analyzed and stratification techniques are employed to address the imbalance during Convolutional Neural Network (CNN) training. Moreover, temporal smoothing is introduced as an online post-processing step to enhance run time prediction. Results: Quantitative analysis is performed on the M2CAI16 tool detection dataset to highlight the importance of stratification, temporal smoothing and the overall framework for tool detection. Conclusion: The analysis on tool imbalance, backed by the empirical results indicates the need and superiority of the proposed framework over state-of-the-art techniques.}, language = {en} } @article{WilsonAnglinAmbellanetal.2017, author = {Wilson, David and Anglin, Carolyn and Ambellan, Felix and Grewe, Carl Martin and Tack, Alexander and Lamecker, Hans and Dunbar, Michael and Zachow, Stefan}, title = {Validation of three-dimensional models of the distal femur created from surgical navigation point cloud data for intraoperative and postoperative analysis of total knee arthroplasty}, volume = {12}, journal = {International Journal of Computer Assisted Radiology and Surgery}, number = {12}, publisher = {Springer}, doi = {10.1007/s11548-017-1630-5}, pages = {2097 -- 2105}, year = {2017}, abstract = {Purpose: Despite the success of total knee arthroplasty there continues to be a significant proportion of patients who are dissatisfied. One explanation may be a shape mismatch between pre and post-operative distal femurs. The purpose of this study was to investigate a method to match a statistical shape model (SSM) to intra-operatively acquired point cloud data from a surgical navigation system, and to validate it against the pre-operative magnetic resonance imaging (MRI) data from the same patients. Methods: A total of 10 patients who underwent navigated total knee arthroplasty also had an MRI scan less than 2 months pre-operatively. The standard surgical protocol was followed which included partial digitization of the distal femur. Two different methods were employed to fit the SSM to the digitized point cloud data, based on (1) Iterative Closest Points (ICP) and (2) Gaussian Mixture Models (GMM). The available MRI data were manually segmented and the reconstructed three-dimensional surfaces used as ground truth against which the statistical shape model fit was compared. Results: For both approaches, the difference between the statistical shape model-generated femur and the surface generated from MRI segmentation averaged less than 1.7 mm, with maximum errors occurring in less clinically important areas. Conclusion: The results demonstrated good correspondence with the distal femoral morphology even in cases of sparse data sets. Application of this technique will allow for measurement of mismatch between pre and post-operative femurs retrospectively on any case done using the surgical navigation system and could be integrated into the surgical navigation unit to provide real-time feedback.}, language = {en} } @article{HoffmannLemanisFalkenbergetal.2017, author = {Hoffmann, Ren{\´e} and Lemanis, Robert and Falkenberg, Janina and Schneider, Steffen and Wesendonk, Hendrik and Zachow, Stefan}, title = {Integrating 2D and 3D shell morphology to disentangle the palaeobiology of ammonoids: A virtual approach}, volume = {61}, journal = {Palaeontology}, number = {1}, doi = {10.1111/pala.12328}, pages = {89 -- 104}, year = {2017}, abstract = {We demonstrate, based on data derived from computed tomography, that integrating 2D and 3D morphological data of ammonoid shells represent an important new approach to disentangle the palaeobiology of ammonoids. Characterization of ammonite morphology has long been constrained to 2D data and only a few studies collect ontogenetic data in 180° steps. We combine this traditional approach with 3D data collected from high-resolution nano-computed tomography. For this approach, ontogenetic morphological data of the hollow shell of a juvenile ammonite Kosmoceras (Jurassic, Callovian) is collected. 2D data is collected in 10° steps and show significant changes in shell morphology. Preserved hollow spines show multiple mineralized membranes never reported before, representing temporal changes of the ammonoid mantle tissue. 3D data show that chamber volumes do not always increase exponentially, as was generally assumed, but may represent a proxy for life events, e.g. stress phases. Furthermore, chamber volume cannot be simply derived from septal spacing in forms comparable to Kosmoceras. Vogel numbers, a 3D parameter for chamber shape, of Kosmoceras are similar to other ammonoids (Arnsbergites, Amauroceras) and modern cephalopods (Nautilus, Spirula). Two methods to virtually document the suture line ontogeny, used to document phylogenetic relationships of larger taxonomic entities, were applied for the first time and seem a promising alternative to hand drawings. The curvature of the chamber surfaces increases during ontogeny due to increasing strength of ornamentation and septal complexity. As increasing curvature may allow for faster handling of cameral liquid, it could compensate for decreasing SA/V ratios through ontogeny.}, language = {en} } @article{BrueningGoubergritsHepptetal.2017, author = {Br{\"u}ning, Jan and Goubergrits, Leonid and Heppt, Werner and Zachow, Stefan and Hildebrandt, Thomas}, title = {Numerical Analysis of Nasal Breathing - A Pilot Study}, volume = {33}, journal = {Facial Plastic Surgery}, number = {4}, doi = {doi:10.1055/s-0037-1603789}, pages = {388 -- 395}, year = {2017}, abstract = {Background: Currently, there is no fully sufficient way to differentiate between symptomatic and normal nasal breathing. Using the nose's total resistance is disputed as a valid means to objectify nasal airflow, and the need for a more comprehensive diagnostic method is increasing. This work's aim was to test a novel approach considering intranasal wall shear stress as well as static pressure maps obtained by computational fluid dynamics (CFD). Methods: X-ray computed tomography (CT) scan data of six symptom-free subjects and seven symptomatic patients were used. Patient-specific geometries of the nasal cavity were segmented from these data sets. Inspiratory and expiratory steady airflow simulations were performed using CFD. Calculated static pressures and wall shear stresses (WSS) were mapped onto a common template of the nasal septum, allowing for comparison of these parameters between the two patient groups. Results: Significant differences in wall shear stress distributions during the inspiratory phase could be identified between the two groups, whereas no differences were found for the expiratory phase. It is assumed that one essential feature of normal nasal breathing probably consists in distinctively different intranasal flow fields for inspiration and expiration. This is in accordance with previous investigations. Conclusion: The proposed method seems to be a promising tool for developing a new kind of patient-specific assessment of nasal breathing. However, more studies and a greater case number of data with an expanded focus, would be ideal.}, language = {en} } @misc{WeiserErdmannSchenkletal.2017, author = {Weiser, Martin and Erdmann, Bodo and Schenkl, Sebastian and Muggenthaler, Holger and Hubig, Michael and Mall, Gita and Zachow, Stefan}, title = {Uncertainty in Temperature-Based Determination of Time of Death}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-63818}, year = {2017}, abstract = {Temperature-based estimation of time of death (ToD) can be per- formed either with the help of simple phenomenological models of corpse cooling or with detailed mechanistic (thermodynamic) heat transfer mod- els. The latter are much more complex, but allow a higher accuracy of ToD estimation as in principle all relevant cooling mechanisms can be taken into account. The potentially higher accuracy depends on the accuracy of tissue and environmental parameters as well as on the geometric resolution. We in- vestigate the impact of parameter variations and geometry representation on the estimated ToD based on a highly detailed 3D corpse model, that has been segmented and geometrically reconstructed from a computed to- mography (CT) data set, differentiating various organs and tissue types. From that we identify the most crucial parameters to measure or estimate, and obtain a local uncertainty quantifcation for the ToD.}, language = {en} } @article{vonTycowiczAmbellanMukhopadhyayetal.2018, author = {von Tycowicz, Christoph and Ambellan, Felix and Mukhopadhyay, Anirban and Zachow, Stefan}, title = {An Efficient Riemannian Statistical Shape Model using Differential Coordinates}, volume = {43}, journal = {Medical Image Analysis}, number = {1}, doi = {10.1016/j.media.2017.09.004}, pages = {1 -- 9}, year = {2018}, abstract = {We propose a novel Riemannian framework for statistical analysis of shapes that is able to account for the nonlinearity in shape variation. By adopting a physical perspective, we introduce a differential representation that puts the local geometric variability into focus. We model these differential coordinates as elements of a Lie group thereby endowing our shape space with a non-Euclidean structure. A key advantage of our framework is that statistics in a manifold shape space becomes numerically tractable improving performance by several orders of magnitude over state-of-the-art. We show that our Riemannian model is well suited for the identification of intra-population variability as well as inter-population differences. In particular, we demonstrate the superiority of the proposed model in experiments on specificity and generalization ability. We further derive a statistical shape descriptor that outperforms the standard Euclidean approach in terms of shape-based classification of morphological disorders.}, language = {en} } @misc{HoffmannSchultzSchellhornetal.2014, author = {Hoffmann, Ren{\´e} and Schultz, Julia A. and Schellhorn, Rico and Rybacki, Erik and Keupp, Helmut and Lemanis, Robert and Zachow, Stefan}, title = {Non-invasive imaging methods applied to neo- and paleo-ontological cephalopod research}, issn = {1438-0064}, doi = {10.5194/bg-11-2721-2014}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-50300}, year = {2014}, abstract = {Several non-invasive methods are common practice in natural sciences today. Here we present how they can be applied and contribute to current topics in cephalopod (paleo-) biology. Different methods will be compared in terms of time necessary to acquire the data, amount of data, accuracy/resolution, minimum/maximum size of objects that can be studied, the degree of post-processing needed and availability. The main application of the methods is seen in morphometry and volumetry of cephalopod shells. In particular we present a method for precise buoyancy calculation. Therefore, cephalopod shells were scanned together with different reference bodies, an approach developed in medical sciences. It is necessary to know the volume of the reference bodies, which should have similar absorption properties like the object of interest. Exact volumes can be obtained from surface scanning. Depending on the dimensions of the study object different computed tomography techniques were applied.}, language = {en} } @misc{EhlkeFrenzelRammetal.2014, author = {Ehlke, Moritz and Frenzel, Thomas and Ramm, Heiko and Lamecker, Hans and Akbari Shandiz, Mohsen and Anglin, Carolyn and Zachow, Stefan}, title = {Robust Measurement of Natural Acetabular Orientation from AP Radiographs using Articulated 3D Shape and Intensity Models}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-49824}, year = {2014}, language = {en} } @article{Zachow2015, author = {Zachow, Stefan}, title = {Computational Planning in Facial Surgery}, volume = {31}, journal = {Facial Plastic Surgery}, number = {5}, doi = {10.1055/s-0035-1564717}, pages = {446 -- 462}, year = {2015}, abstract = {This article reflects the research of the last two decades in computational planning for cranio-maxillofacial surgery. Model-guided and computer-assisted surgery planning has tremendously developed due to ever increasing computational capabilities. Simulators for education, planning, and training of surgery are often compared with flight simulators, where maneuvers are also trained to reduce a possible risk of failure. Meanwhile, digital patient models can be derived from medical image data with astonishing accuracy and thus can serve for model surgery to derive a surgical template model that represents the envisaged result. Computerized surgical planning approaches, however, are often still explorative, meaning that a surgeon tries to find a therapeutic concept based on his or her expertise using computational tools that are mimicking real procedures. Future perspectives of an improved computerized planning may be that surgical objectives will be generated algorithmically by employing mathematical modeling, simulation, and optimization techniques. Planning systems thus act as intelligent decision support systems. However, surgeons can still use the existing tools to vary the proposed approach, but they mainly focus on how to transfer objectives into reality. Such a development may result in a paradigm shift for future surgery planning.}, language = {en} } @misc{LamasRodriguezEhlkeHoffmannetal.2015, author = {Lamas-Rodr{\´i}guez, Juli{\´a}n and Ehlke, Moritz and Hoffmann, Ren{\´e} and Zachow, Stefan}, title = {GPU-accelerated denoising of large tomographic data sets with low SNR}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-56339}, year = {2015}, abstract = {Enhancements in tomographic imaging techniques facilitate non-destructive methods for visualizing fossil structures. However, to penetrate dense materials such as sediments or pyrites, image acquisition is typically performed with high beam energy and very sensitive image intensifiers, leading to artifacts and noise in the acquired data. The analysis of delicate fossil structures requires the images to be captured in maximum resolution, resulting in large data sets of several giga bytes (GB) in size. Since the structural information of interest is often almost in the same spatial range as artifacts and noise, image processing and segmentation algorithms have to cope with a very low signal-to-noise ratio (SNR). Within this report we present a study on the performance of a collection of denoising algorithms applied to a very noisy fossil dataset. The study shows that a non-local means (NLM) filter, in case it is properly configured, is able to remove a considerable amount of noise while preserving most of the structural information of interest. Based on the results of this study, we developed a software tool within ZIBAmira that denoises large tomographic datasets using an adaptive, GPU-accelerated NLM filter. With the help of our implementation a user can interactively configure the filter's parameters and thus its effectiveness with respect to the data of interest, while the filtering response is instantly visualized for a preselected region of interest (ROI). Our implementation efficiently denoises even large fossil datasets in a reasonable amount of time.}, language = {en} } @incollection{LameckerZachow2016, author = {Lamecker, Hans and Zachow, Stefan}, title = {Statistical Shape Modeling of Musculoskeletal Structures and Its Applications}, volume = {23}, booktitle = {Computational Radiology for Orthopaedic Interventions}, publisher = {Springer}, isbn = {978-3-319-23481-6}, doi = {10.1007/978-3-319-23482-3}, pages = {1 -- 23}, year = {2016}, abstract = {Statistical shape models (SSM) describe the shape variability contained in a given population. They are able to describe large populations of complex shapes with few degrees of freedom. This makes them a useful tool for a variety of tasks that arise in computer-aided madicine. In this chapter we are going to explain the basic methodology of SSMs and present a variety of examples, where SSMs have been successfully applied.}, language = {en} } @article{ZachowHeppt2015, author = {Zachow, Stefan and Heppt, Werner}, title = {The Facial Profile}, volume = {31}, journal = {Facial Plastic Surgery}, number = {5}, doi = {10.1055/s-0035-1566132}, pages = {419 -- 420}, year = {2015}, abstract = {Facial appearance in our societies is often associated with notions of attractiveness, juvenileness, beauty, success, and so forth. Hence, the role of facial plastic surgery is highly interrelated to a patient's desire to feature many of these positively connoted attributes, which of course, are subject of different cultural perceptions or social trends. To judge about somebody's facial appearance, appropriate quantitative measures as well as methods to obtain and compare individual facial features are required. This special issue on facial profile is intended to provide an overview on how facial characteristics are surgically managed in an interdisciplinary way based on experience, instrumentation, and modern technology to obtain an aesthetic facial appearance with harmonious facial proportions. The facial profile will be discussed within the context of facial aesthetics. Latest concepts for capturing facial morphology in high speed and impressive detail are presented for quantitative analysis of even subtle changes, aging effects, or facial expressions. In addition, the perception of facial profiles is evaluated based on eye tracking technology.}, language = {en} } @article{ZahnGrotjohannRammetal.2015, author = {Zahn, Robert and Grotjohann, Sarah and Ramm, Heiko and Zachow, Stefan and Putzier, Michael and Perka, Carsten and Tohtz, Stephan}, title = {Pelvic tilt compensates for increased acetabular anteversion}, volume = {40}, journal = {International Orthopaedics}, number = {8}, doi = {10.1007/s00264-015-2949-6}, pages = {1571 -- 1575}, year = {2015}, abstract = {Pelvic tilt determines functional orientation of the acetabulum. In this study, we investigated the interaction of pelvic tilt and functional acetabular anteversion (AA) in supine position.}, language = {en} } @misc{GuentherLameckerWeiser2011, author = {G{\"u}nther, Andreas and Lamecker, Hans and Weiser, Martin}, title = {Direct LDDMM of Discrete Currents with Adaptive Finite Elements}, journal = {Proceedings of the Third International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Modelling Biological Shape Variability}, editor = {Pennec, X. and Joshi, S. and Nielsen, M.}, pages = {1 -- 14}, year = {2011}, abstract = {We consider Large Deformation Diffeomorphic Metric Mapping of general \$m\$-currents. After stating an optimization algorithm in the function space of admissable morph generating velocity fields, two innovative aspects in this framework are presented and numerically investigated: First, we spatially discretize the velocity field with conforming adaptive finite elements and discuss advantages of this new approach. Second, we directly compute the temporal evolution of discrete \$m\$-current attributes.}, language = {en} } @inproceedings{MukhopadhyayOksuzBevilacquaetal.2015, author = {Mukhopadhyay, Anirban and Oksuz, Ilkay and Bevilacqua, Marco and Dharmakumar, Rohan and Tsaftaris, Sotirios}, title = {Data-Driven Feature Learning for Myocardial Segmentation of CP-BOLD MRI}, volume = {9126}, booktitle = {Functional Imaging and Modeling of the Heart}, publisher = {Springer}, doi = {10.1007/978-3-319-20309-6_22}, pages = {189 -- 197}, year = {2015}, abstract = {Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP- BOLD) MR is capable of diagnosing an ongoing ischemia by detecting changes in myocardial intensity patterns at rest without any contrast and stress agents. Visualizing and detecting these changes require significant post-processing, including myocardial segmentation for isolating the myocardium. But, changes in myocardial intensity pattern and myocardial shape due to the heart's motion challenge automated standard CINE MR myocardial segmentation techniques resulting in a significant drop of segmentation accuracy. We hypothesize that the main reason behind this phenomenon is the lack of discernible features. In this paper, a multi scale discriminative dictionary learning approach is proposed for supervised learning and sparse representation of the myocardium, to improve the myocardial feature selection. The technique is validated on a challenging dataset of CP-BOLD MR and standard CINE MR acquired in baseline and ischemic condition across 10 canine subjects. The proposed method significantly outperforms standard cardiac segmentation techniques, including segmentation via registration, level sets and supervised methods for myocardial segmentation.}, language = {en} } @inproceedings{MukhopadhyayOksuzBevilacquaetal.2015, author = {Mukhopadhyay, Anirban and Oksuz, Ilkay and Bevilacqua, Marco and Dharmakumar, Rohan and Tsaftaris, Sotirios}, title = {Unsupervised myocardial segmentation for cardiac MRI}, volume = {LNCS 9351}, booktitle = {Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015}, doi = {10.1007/978-3-319-24574-4_2}, pages = {12 -- 20}, year = {2015}, abstract = {Though unsupervised segmentation was a de-facto standard for cardiac MRI segmentation early on, recently cardiac MRI segmentation literature has favored fully supervised techniques such as Dictionary Learning and Atlas-based techniques. But, the benefits of unsupervised techniques e.g., no need for large amount of training data and better potential of handling variability in anatomy and image contrast, is more evident with emerging cardiac MR modalities. For example, CP-BOLD is a new MRI technique that has been shown to detect ischemia without any contrast at stress but also at rest conditions. Although CP-BOLD looks similar to standard CINE, changes in myocardial intensity patterns and shape across cardiac phases, due to the heart's motion, BOLD effect and artifacts affect the underlying mechanisms of fully supervised segmentation techniques resulting in a significant drop in segmentation accuracy. In this paper, we present a fully unsupervised technique for segmenting myocardium from the background in both standard CINE MR and CP-BOLD MR. We combine appearance with motion information (obtained via Optical Flow) in a dictionary learning framework to sparsely represent important features in a low dimensional space and separate myocardium from background accordingly. Our fully automated method learns background-only models and one class classifier provides myocardial segmentation. The advantages of the proposed technique are demonstrated on a dataset containing CP-BOLD MR and standard CINE MR image sequences acquired in baseline and ischemic condition across 10 canine subjects, where our method outperforms state-of-the-art supervised segmentation techniques in CP-BOLD MR and performs at-par for standard CINE MR.}, language = {en} } @inproceedings{OksuzMukhopadhyayBevilacquaetal.2015, author = {Oksuz, Ilkay and Mukhopadhyay, Anirban and Bevilacqua, Marco and Dharmakumar, Rohan and Tsaftaris, Sotirios}, title = {Dictionary Learning Based Image Descriptor for Myocardial Registration of CP-BOLD MR}, volume = {9350}, booktitle = {Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015}, publisher = {Springer}, doi = {10.1007/978-3-319-24571-3_25}, pages = {205 -- 213}, year = {2015}, abstract = {Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP- BOLD) MRI is a new contrast agent- and stress-free imaging technique for the assessment of myocardial ischemia at rest. The precise registration among the cardiac phases in this cine type acquisition is essential for automating the analysis of images of this technique, since it can potentially lead to better specificity of ischemia detection. However, inconsistency in myocardial intensity patterns and the changes in myocardial shape due to the heart's motion lead to low registration performance for state- of-the-art methods. This low accuracy can be explained by the lack of distinguishable features in CP-BOLD and inappropriate metric defini- tions in current intensity-based registration frameworks. In this paper, the sparse representations, which are defined by a discriminative dictionary learning approach for source and target images, are used to improve myocardial registration. This method combines appearance with Gabor and HOG features in a dictionary learning framework to sparsely represent features in a low dimensional space. The sum of squared differences of these distinctive sparse representations are used to define a similarity term in the registration framework. The proposed descriptor is validated on a challenging dataset of CP-BOLD MR and standard CINE MR acquired in baseline and ischemic condition across 10 canines.}, language = {en} } @inproceedings{SalehSahuZafaretal.2015, author = {Saleh, Salah and Sahu, Manish and Zafar, Zuhair and Berns, Karsten}, title = {A Multimodal Nonverbal Human-robot Communication System}, booktitle = {VI International Conference on Computational Bioengineering}, year = {2015}, abstract = {Socially interactive robot needs the same behaviors and capabilities of human to be accepted as a member in human society. The environment, in which this robot should operate, is the human daily life. The interaction capabilities of current robots are still limited due to complex inter-human interaction system. Humans usually use different types of verbal and nonverbal cues in their communication. Facial expression and head movement are good examples of nonverbal cues used in feedback. This paper presents a biological inspired system for Human-Robot Interaction (HRI). This system is based on the interactive model of inter-human communication proposed by Schramm. In this model, the robot and its interaction partner can be send and receive information at the same time. For example, if the robot is talking, it also perceive the feedback of the human via his/her nonverbal cues. In this work, we are focusing on recognizing the facial expression of human. The proposed facial expression recognition technique is based on machine learning. Multi SVMs have been used to recognize the six basic emotions in addition to the neutral expression. This technique uses only the depth information, acquired by Kinect, of human face.}, language = {en} }