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Weismann-Netter-Stuhl (WNS) syndrome is a rare skeletal anomaly that affects the diaphyseal part of both the tibiae and fibulae with posterior cortical thickening and anteroposterior bowing. This anomaly is usually bilateral and symmetrical. The patients are generally of short stature. In some cases, a family history suggesting genetic transmission of a mutation with an unknown locus has been reported. In this paper we present an infant with WNS syndrome with bilateral involvement of the femur. Similar clinical findings were defined in three other family members.

Conflict of interest:None declared.

We describe a neuro imaging protocol that utilizes an anatomical atlas of the human head to guide Diffuse optical tomography of human brain activation. The protocol is demonstrated by imaging the hemodynamic response to median nerve stimulation in three healthy subjects, and comparing the images obtained using a head atlas with the images obtained using the subject-specific head anatomy. The results indicate that using the head atlas anatomy it is possible to reconstruct the location of the brain activation to the expected gyrus of the brain, in agreement with the results obtained with the subject-specific head anatomy. The benefits of this novel method derive from eliminating the need for subject-specific head anatomy and thus obviating the need for a subject-specific MRI to improve the anatomical interpretation of Diffuse optical tomography images of brain activation.

The ‘Atlas of Genetics and Cytogenetics in Oncology and Haematology’ (http://www.infobiogen.fr/services/chromcancer) contains concise and updated cards on genes involved in cancer, cytogenetics and clinical entities in oncology, and cancer-prone diseases, a portal towards genetics/cancer, and teaching materials in genetics. This database is made for and by researchers and clinicians, who are encouraged to contribute. The Atlas is part of the genome project and it participates in research on cancer epidemiology.

The ‘Atlas of Genetics and Cytogenetics in Oncology and Haematology’ (http://www.infobiogen.fr/services/ chromcancer ) is a database devoted to chromosome abnormalities in cancer, cancer-prone diseases and genes involved in cancer. Information presented in each page is concise and updated. This database is made for and by: cytogeneticists, molecular biologists, clinicians in oncology and in haematology, and pathologists, who are encouraged to contribute.

The ‘Atlas of Genetics and Cytogenetics in Oncology and Haematology’ (http://www.infobiogen.fr/services/chromcancer) is an Internet database aimed at genes involved in cancer, cytogenetics and clinical entities in cancer, and cancer-prone diseases. It presents information in concise and updated reviews (cards) or longer texts (deep insights), a (new) case report section, a huge portal towards genetics and/or cancer databases, and teaching items in genetics for students in medicine and the sciences. This database is made for and by clinicians and researchers in the above-mentioned fields, who are encouraged to contribute. It deals with cancer research, genomics and cytogenomics. It is at the crossroads of research, post-university teaching and telemedicine. The Atlas is available at no cost.

This CD-ROM version of Atlas of Salivary Gland Tumor Cytopathology, Oral & Surgical Pathology is an excellent and concise tool for easy reference during sign out of cytology and surgical cases. It is also invaluable as a teaching tool for residents and fellows.

Atlas of Salivary Gland Tumor Cytopathology, Oral & Surgical Pathology CD-ROM (ISBN 0-9736518-0-7), Published by Pathology images Inc Ottawa, Ontario K2B 7L4, Canada

Hypertext atlas of fetal and neonatal pathology is a free resource for pregraduate students of medicine, pathologists and other health professionals dealing with prenatal medicine. The atlas can be found at . The access is restricted to registered users. Concise texts summarize the gross and microscopic pathology, etiology, and clinical signs of both common and rare fetal and neonatal conditions. The texts are illustrated with over 300 images that are accompanied by short comments. The atlas offers histological pictures of high quality. Virtual microscope interface is used to access the high-resolution histological images. Fetal ultrasound video clips are included. Case studies integrate clinical history, prenatal ultrasonographic examination, gross pathology and histological features. The atlas is available in English (and Czech) and equipped with an active index. The atlas is suitable both for medical students and pathologists as a teaching and reference tool. The atlas is going to be further expanded while keeping the high quality of the images.

A World Wide Web Common Gateway Interface package is described for accessing existing online interactive atlases of anatomy. The Web interface accesses the same 2-D and 3-D images of human neuroanatomy, knee anatomy and thoracic viscera that are currently accessed by a custom interactive atlas in distance learning courses. Although the Web interface is too slow to replace the existing atlas, it provides a parallel access path that has much broader potential for development of a distributed distance learning network in anatomy. By maintaining both access methods to the same information sources we continue to satisfy the fast interactivity needs for our local courses, while at the same time providing a migration path to the Web as the capabilities of Web browsers evolve.

Images

ATLAS-plus [Advanced Tools for Learning Anatomical Structure] is a multimedia program used to assist in the teaching of anatomy at the University of Michigan Medical School. ATLAS-plus contains three courses: Histology, Embryology, and Gross Anatomy. In addition to the three courses, a glossary containing terms from the three courses is available. All three courses and the glossary are accessible in the ATLAS-plus environment. The ATLAS-plus environment provides a consistent set of tools and options so that the user can navigate easily and intelligently in and between the various courses and modules in the ATLAS-plus world. The program is a collaboration between anatomy and cell biology faculty, medical students, graphic artists, systems analysts, and instructional designers.

Conflicts can occur between the principle of freedom of information treasured by librarians and ethical standards of scientific research involving the propriety of using data derived from immoral or dishonorable experimentation. A prime example of this conflict was brought to the attention of the medical and library communities in 1995 when articles claiming that the subjects of the illustrations in the classic anatomy atlas, Eduard Pernkopf's Topographische Anatomie des Menschen, were victims of the Nazi holocaust. While few have disputed the accuracy, artistic, or educational value of the Pernkopf atlas, some have argued that the use of such subjects violates standards of medical ethics involving inhuman and degrading treatment of subjects or disrespect of a human corpse. Efforts were made to remove the book from medical libraries. In this article, the history of the Pernkopf atlas and the controversy surrounding it are reviewed. The results of a survey of academic medical libraries concerning their treatment of the Pernkopf atlas are reported, and the ethical implications of these issues as they affect the responsibilities of librarians is discussed.

Structural delineation and assignment are the fundamental steps in understanding the anatomy of the human brain. The white matter has been structurally defined in the past only at its core regions (deep white matter). However, the most peripheral white matter areas, which are interleaved between the cortex and the deep white matter, have lacked clear anatomical definitions and parcellations. We used axonal fiber alignment information from diffusion tensor imaging (DTI) to delineate the peripheral white matter, and investigated its relationship with the cortex and the deep white matter. Using DTI data from 81 healthy subjects, we identified nine common, blade-like anatomical regions, which were further parcellated into 21 subregions based on the cortical anatomy. Four short association fiber tracts connecting adjacent gyri (U-fibers) were also identified reproducibly among the healthy population. We anticipate that this atlas will be useful resource for atlas-based white matter anatomical studies.

One of the primary goals of computational anatomy is the statistical analysis of anatomical variability in large populations of images. The study of anatomical shape is inherently related to the construction of transformations of the underlying coordinate space, which map one anatomy to another. It is now well established that representing the geometry of shapes or images in Euclidian spaces undermines our ability to represent natural variability in populations. In our previous work we have extended classical statistical analysis techniques, such as averaging, principal components analysis, and regression, to Riemannian manifolds, which are more appropriate representations for describing anatomical variability. In this paper we extend the notion of robust estimation, a well established and powerful tool in traditional statistical analysis of Euclidian data, to manifold-valued representations of anatomical variability. In particular, we extend the geometric median, a classic robust estimator of centrality for data in Euclidean spaces. We formulate the geometric median of data on a Riemannian manifold as the minimizer of the sum of geodesic distances to the data points. We prove existence and uniqueness of the geometric median on manifolds with non-positive sectional curvature and give sufficient conditions for uniqueness on positively curved manifolds. Generalizing the Weiszfeld procedure for finding the geometric median of Euclidean data, we present an algorithm for computing the geometric median on an arbitrary manifold. We show that this algorithm converges to the unique solution when it exists. In this paper we exemplify the robustness of the estimation technique by applying the procedure to various manifolds commonly used in the analysis of medical images. Using this approach, we also present a robust brain atlas estimation technique based on the geometric median in the space of deformable images.

Although various posterior insertion angles for screw insertion have been proposed for C1 lateral mass, substantial conclusions have not been reached regarding ideal angles and average length of the screw yet. We aimed to re-consider the morphometry and the ideal trajections of the C1 screw. Morphometric analysis was performed on 40 Turkish dried atlas vertebrae obtained from the Department of Anatomy at the Medical School of Ankara University. The quantitative anatomy of the screw entry zone, trajectories, and the ideal lengths of the screws were calculated to evaluate the feasibility of posterior screw fixation of the lateral mass of the atlas. The entry point into the lateral mass of the atlas is the intersection of the posterior arch and the C1 lateral mass. The optimum medial angle is 13.5 ± 1.9° and maximal angle of medialization is 29.4 ± 3.0°. The ideal cephalic angle is 15.2 ± 2.6°, and the maximum cephalic angle is 29.6 ± 2.6°. The optimum screw length was found to be 19.59 ± 2.20 mm. With more than 30° of medial trajections and cephalic trajections the screw penetrates into the spinal canal and atlantooccipital joint, respectively. Strikingly, in 52% of our specimens, the height of the inferior articular process was under 3.5 mm, and in 70% was under 4 mm, which increases the importance of the preparation of the screw entry site. For accommodation of screws of 3.5-mm in diameter, the starting point should be taken as the insertion of the posterior arch at the superior end of the inferior articular process with a cephalic trajection. This study may aid many surgeons in their attempts to place C1 lateral mass screws.

Estimation of internal mouse anatomy is required for quantitative bioluminescence or fluorescence tomography. However, only surface range data can be recovered from all-optical systems. These data are at times sparse or incomplete. We present a method for fitting an elastically deformable mouse atlas to surface topographic range data acquired by an optical system. In this method, we first match the postures of a deformable atlas and the range data of the mouse being imaged. This is achieved by aligning manually identified landmarks. We then minimize the asymmetric L2 pseudo-distance between the surface of the deformable atlas and the surface topography range data. Once this registration is accomplished, the internal anatomy of the atlas is transformed to the coordinate system of the range data using elastic energy minimization. We evaluated our method by using it to register a digital mouse atlas to a surface model produced from a manually labeled CT mouse data set. Dice coefficents indicated excellent agreement in the brain and heart, with fair agreement in the kidneys and bladder. We also present example results produced using our method to align the digital mouse atlas to surface range data.

For pre-clinical bioluminescence or fluorescence optical tomography, the animal's surface topography and internal anatomy need to be estimated for improving the quantitative accuracy of reconstructed images. The animal's surface profile can be measured by all-optical systems, but estimation of the internal anatomy using optical techniques is non-trivial. A 3D anatomical mouse atlas may be warped to the estimated surface. However, fitting an atlas to surface topography data is challenging because of variations in the posture and morphology of imaged mice. In addition, acquisition of partial data (for example, from limited views or with limited sampling) can make the warping problem ill-conditioned. Here, we present a method for fitting a deformable mouse atlas to surface topographic range data acquired by an optical system. As an initialization procedure, we match the posture of the atlas to the posture of the mouse being imaged using landmark constraints. The asymmetric L2 pseudo-distance between the atlas surface and the mouse surface is then minimized in order to register two data sets. A Laplacian prior is used to ensure smoothness of the surface warping field. Once the atlas surface is normalized to match the range data, the internal anatomy is transformed using elastic energy minimization. We present results from performance evaluation studies of our method where we have measured the volumetric overlap between the internal organs delineated directly from MRI or CT and those estimated by our proposed warping scheme. Computed Dice coefficients indicate excellent overlap in the brain and the heart, with fair agreement in the kidneys and the bladder.

We have developed a method for automated probabilistic reconstruction of a set of major white-matter pathways from diffusion-weighted MR images. Our method is called TRACULA (TRActs Constrained by UnderLying Anatomy) and utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual interaction with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. In this paper we illustrate the application of the method on data from a schizophrenia study and investigate whether the inclusion of both patients and healthy subjects in the training set affects our ability to reconstruct the pathways reliably. We show that, since our method does not constrain the exact spatial location or shape of the pathways but only their trajectory relative to the surrounding anatomical structures, a set a of healthy training subjects can be used to reconstruct the pathways accurately in patients as well as in controls.

eMouseAtlas (www.emouseatlas.org) is a comprehensive online resource to visualise mouse development and investigate gene expression in the mouse embryo. We have recently deployed a completely redesigned Mouse Anatomy Atlas website (www.emouseatlas.org/emap/ema) that allows users to view 3D embryo reconstructions, delineated anatomy, and high-resolution histological sections. A new feature of the website is the IIP3D web tool that allows a user to view arbitrary sections of 3D embryo reconstructions using a web browser. This feature provides interactive access to very high-volume 3D images via a tiled pan-and-zoom style interface and circumvents the need to download large image files for visualisation. eMouseAtlas additionally includes EMAGE (Edinburgh Mouse Atlas of Gene Expression) (www.emouseatlas.org/emage), a freely available, curated online database of in situ gene expression patterns, where gene expression domains extracted from raw data images are spatially mapped into atlas embryo models. In this way, EMAGE introduces a spatial dimension to transcriptome data and allows exploration of the spatial similarity between gene expression patterns. New features of the EMAGE interface allow complex queries to be built, and users can view and compare multiple gene expression patterns. EMAGE now includes mapping of 3D gene expression domains captured using the imaging technique optical projection tomography. 3D mapping uses WlzWarp, an open-source software tool developed by eMouseAtlas.

Most diffusion imaging studies have used subject registration to an atlas space for enhanced quantification of anatomy. However, standard diffusion tensor atlases lack information in regions of fiber crossing and are based on adult anatomy. The degree of error associated with applying these atlases to studies of children for example has not yet been estimated but may lead to suboptimal results. This paper describes a novel technique for generating population-specific high angular resolution diffusion imaging (HARDI)-based atlases consisting of labeled regions of homogenous white matter. Our approach uses a fiber orientation distribution (FOD) diffusion model and a data driven clustering algorithm. White matter regional labeling is achieved by our automated data driven clustering algorithm that has the potential to delineate white matter regions based on fiber complexity and orientation. The advantage of such an atlas is that it is study specific and more comprehensive in describing regions of white matter homogeneity as compared to standard anatomical atlases. We have applied this state of the art technique to a dataset consisting of adolescent and preadolescent children, creating one of the first examples of a HARDI-based atlas, thereby establishing the feasibility of the atlas creation framework. The white matter regions generated by our automated clustering algorithm have lower FOD variance than when compared to the regions created from a standard anatomical atlas.

We report a very rare case of a congenital cervical spine anomaly. The low occurrence rate of this anatomic variant combined with the high frequency of cervical injuries in sports medicine made this case a diagnostic challenge on both emergency and orthopaedic departments. After reading, it should give the clinician a more consistent view in differentiating the traumatic or congenital origin of the disorder seen on radiographs, as well as what can be expected in the future when diagnosis is set.

EMAGE (http://genex.hgu.mrc.ac.uk/Emage/database) is a database of in situ gene expression patterns in the developing mouse embryo. Domains of expression from raw data images are spatially integrated into a set of standard 3D virtual mouse embryos at different stages of development, allowing data interrogation by spatial methods. Sites of expression are also described using an anatomy ontology and data can be queried using text-based methods. Here we describe recent enhancements to EMAGE which include advances in spatial search methods including: a refined local spatial similarity search algorithm, a method to allow global spatial comparison of patterns in EMAGE and subsequent hierarchical-clustering, and spatial searches across multiple stages of development. In addition, we have extended data access by the introduction of web services and new HTML-based search interfaces, which allow access to data that has not yet been spatially annotated. We have also started incorporating full 3D images of gene expression that have been generated using optical projection tomography (OPT).

Elastic image registration is widely used to adapt brain images to a common template space, and, in complementary fashion, to adapt an anatomical template to a subject's anatomy. Although HAMMER is a very accurate image-registration algorithm, it requires a 3-class segmentation step prior to registration, and its performance is affected by segmentation quality. We here propose a new framework to improve this algorithm's robustness to poor initial segmentation. Our new framework is based on Adaptive Generalized Expectation Maximization (AGEM) for unified segmentation and registration, in which we use an adaptive strategy to incorporate spatial information from a probabilistic atlas to improve segmentation and registration simultaneously. Our experiments using real MR brain images indicate that our integrated approach improves registration accuracy; we have also found that our iterative approach renders HAMMER robust to low tissue contrast, which hinders 3-class segmentation.