Digital Anatomy

Anatomy studies the morphology and structure of organisms. The word originates from the Greek ana-, up; and tome-, meaning cutting. As its name implies, anatomy relies heavily on dissection and studies the human body parts’ arrangement and interaction. Heir from a rich Greco-Roman tradition and background, Vesalius (1543) is arguably the father of modern anatomy (Fig. 1.1). Since its early origins, there has been a clear connection between the study of anatomy, graphics depictions, and illustrative visualizations. True to its origins, computer-based three-dimensional modeling of the human body, also known as Digital Anatomy, has strong visualization roots. Digital Anatomy has benefited from the computer and communications technological revolution. It lies at the intersection of converging different disciplines, ranging from Medical Imaging, Medical Visualization, 3D printing, and Computer Graphics to Artificial Intelligence and Robotics. This book offers a perspective on current developments and a road map into the future for this exciting pillar of modern medicine.

As the oldest medical craft, anatomy remains the core and foundational field of medicine. That is why anatomy is in perpetual advancement, thanks to the technical progress in exploring the human body through computer science and biomedical research. Knowledge of the human body is the basis of medicine. Classical cadaver dissection, the standard discovery tool for centuries, is both unique and destructive of the surrounding tissues. For many years, anatomists have sought to preserve the shape of dissected organs for reference, teaching, and further inspection through different methods. Wax models make a copy of selected dissections. Vessel or duct injection with resin is another dissection-preserving technique. However, all these anatomical objects are unique in time and frozen in place. In contrast, modern Digital Anatomy aims to preserve structures from dissection in flexible ways. Then deliver the results quickly, flexibly, reproducibly, and interactively via advanced digital tools. Thus, computer-aided anatomical dissection addresses the limitations of classical dissection. Through it, experienced anatomists recognize the structures previously segmented with dedicated software to create accurate 3D models from macro or microscopic slices. Its interactivity, flexibility, and endless reusability make digital dissection a perfect tool for educational anatomy. This chapter explores the history of anatomical studies from their inception to the twenty-first century related to the remainder of the book.

3D reconstruction from anatomical slices permits anatomists to create three-dimensional depictions of real structures by tracing organs from sequences of cryosections. A wide variety of tools for 3D reconstruction from anatomical slices are becoming available for use in training and study. In this chapter, we present Anatomy Studio, a collaborative Mixed Reality tool for virtual dissection that combines tablets with styli and see-through head-mounted displays to assist anatomists by easing manual tracing and exploring cryosection images. By using mid-air interactions and interactive surfaces, anatomists can easily access any cryosection and edit contours, while following other user’s contributions. A user study including experienced anatomists and medical professionals, conducted in real working sessions, demonstrates that Anatomy Studio is appropriate and useful for 3D reconstruction. Results indicate that Anatomy Studio encourages closely coupled collaborations and group discussion, to achieve deeper insights.

Computer-Assisted Anatomical Dissection (CAAD) is a new method of 3D reconstruction of anatomical structures from histological or anatomical slices. It uses staining and immunomarking of the tissues for a more precise identification, in particular for the nerves and the vessels, leading to an easy morphological segmentation. Starting from a digitalized series of transverse histological sections, we perform a staining by immune-markers (protein S100, VAChT and D2-40), then alignment of the slices and finally a manual segmentation of the main anatomical structures by using the Winsurf® software version 3.5. This chapter shows the results of CAAD in embryology and for the pelvic nerves in adults. Its main interest is in the field of pelvic surgery for cancer, to improve the knowledge of the pelvic nervous anatomy and preserve the inferior hypogastric plexus. It is also an original method to provide 3D reconstruction of the human embryo, and so bring us an improved understanding of embryogenesis.

Volume Rendering (VR) from Digital Imaging and Communications in Medicine (DICOM®) data is a powerful source for the analysis and virtual representation of the human anatomy. To achieve this, accurate virtual dissections must be performed by applying the tools and different reconstruction methods offered by Volume Rendering Techniques (VRT).

Teaching morphological sciences’ suffers from the lack of human corpses for dissection due to ethical or religious issues, worsened by increasing students’ demand for educational anatomy. Fortunately, the technological revolution now put at our disposal new virtual reality tools to teach and learn anatomy. These multimedia tools are changing the way students engage and interact with learning material: they can engage in meaningful experiences and gain knowledge. This evolution is particularly true for the virtual dissection table, based on 3D vectorial atlases of the human body. This chapter describes the manual segmentation methodology from the anatomical slices of the Korean visible human project with Winsurf^® software. Although using the same slices, our segmentation technique and refinement of the 3D meshes are quite different from the Korean team (Ajou University, Séoul, Korea). The resulting 3D vectorial models of the whole body of men and women include 1300 anatomical objects. After improvement with a modeler (Blender^® version 4.79), we export 3D atlas into a “.u3d” format to take advantage of the powerful interface of the 3Dpdf Acrobat^® file working in four different languages. The user interface is simplified by a touch screen to manipulate and dissect the virtual body with three fingers easily. Anatomical regions, systems, and structures are selected and controlled by javascript buttons. We developed this educational project under the Auspices of the Unesco chair of digital anatomy (www.​anatomieunesco.​org).

Many fields have adopted 3D technologies, and medicine is no exception. Their use ranges from educational purposes to skill training and clinical applications. This chapter proposes a possible protocol related to obtaining 3D anatomical models from Computed Tomography Angiogram (CTA) data and its subsequent 3D printing. We describe relevant features of free software available for this process as an introductory guide to those who want to make their first steps. We briefly discuss some of the benefits and drawbacks of applying 3D anatomy in pedagogical and surgical areas.

Computed Tomography (CT) is a commonly used imaging modality across a wide variety of diagnostic procedures (World Health Organisation 2017). By generating contiguous cross-sectional images of a body region, CT has the ability to represent valuable 3D data that enables professionals to easily identify, locate, and accurately describe anatomical landmarks. Based on 3D modeling techniques developed by the field of Computer Graphics, the Region of Interest (ROI) can be extracted from the 2D anatomical slices and used to reconstruct subject-specific 3D models. This chapter describes a 3D reconstruction pipeline that can be used to generate 3D models from CT images and also volume renderings for medical visualization purposes (Ribeiro et al. 2009). We will provide several examples on how to segment 3D anatomical structures with high-contrast detail, namely skull, mandible, trachea, and colon, relying solely on the following set of free and open-source tools: ITK-SNAP (Yushkevich et al. 2006) and ParaView (Ahrens et al. 2005).

Computational anatomy is an emerging discipline at the interface of geometry, statistics, and medicine that aims at analyzing and modeling the biological variability of organs’ shapes at the population level. Shapes are equivalence classes of images, surfaces, or deformations of a template under rigid body (or more general) transformations. Thus, they belong to non-linear manifolds. In order to deal with multiple samples in non-linear spaces, a consistent statistical framework on Riemannian manifolds has been designed over the last decade. We detail in this chapter the extension of this framework to Lie groups endowed with the affine symmetric connection, a more invariant (and thus more consistent) but non-metric structure on transformation groups. This theory provides strong theoretical bases for the use of one-parameter subgroups and diffeomorphisms parametrized by stationary velocity fields (SVF), for which efficient image registration methods like log-Demons have been developed with a great success from the practical point of view. One can further reduce the complexity with locally affine transformations, leading to parametric diffeomorphisms of low dimension encoding the major shape variability. We illustrate the methodology with the modeling of the evolution of the brain with Alzheimer’s disease and the analysis of the cardiac motion from MRI sequences of images.

The ability to express emotion through facial gestures impacts social and mental health. The production of these gestures is the result of the individual function and complex synergistic activities of the muscles of facial expression. Visualization and modelling techniques provide insight into how the muscles individually and collectively contribute to the shaping and stiffening of facial soft tissues. However, due to lack of detailed anatomical data, modellers are left to heuristically define the inner structure of each muscle, often resulting in a relatively homogeneous distribution of muscle fibres, which may not be accurate. Recent technological advances have enabled the reconstruction of entire muscles in 3D space as In situ using dissection, digitization and 3D modelling at the fibre bundle/aponeurosis level. In this chapter, we describe the use of this technology to visualize the muscles of facial expression and mastication at the fibre bundle level. The comprehensive 3D model provides novel insights into the asymmetry and complex interrelationships of the individual muscles of facial expression. These data possess great value to improve the anatomical fidelity of biomechanical models, and subsequently simulations, of facial gestures. Furthermore, these data could advance imaging and image processing techniques that are used to derive models.

Cancer is the cause of over 16% of deaths globally. A common form of cancer treatment is radiation therapy; however, students learning radiation therapy have limited access to practical training opportunities due to the high demand upon equipment. Simulation of radiation therapy can provide an effective training solution without requiring expensive and in-demand equipment. We have developed LINACVR, a Virtual Reality radiation (VR) therapy simulation prototype that provides an immersive training solution. We evaluated LINACVR with 15 radiation therapy students and educators. The results indicated that LINACVR would be effective in radiation therapy training and was more effective than existing simulators. The implication of our design is that VR simulation could help to improve the education process of learning about domain-specific health areas such as radiation therapy.

While the usefulness of 3D visualizations has been shown for a range of clinical applications such as treatment planning it still had difficulties in being adopted in widespread clinical practice. This chapter describes how multi-touch surfaces with patient-specific data have contributed to breaking this barrier, paving the way for adoption into clinical practice and, at the same time, also found widespread use in educational settings and in communication of science to the general public. The key element identified for this adoption is the string of steps found in the full imaging chain, which will be described as an introduction to the topic in this chapter. Emphasis in the chapter is, however, visualization aspects, e.g., intuitive interaction with patient-specific data captured with the latest high speed and high-quality imaging modalities. A necessary starting point for this discussion is the foundations of and state-of-the-art in volumetric rendering, which form the basis for the underlying theory part of the chapter. The chapter presents two use cases. One case is focusing on the use of multi-touch in medical education and the other is focusing on the use of touch surfaces at public venues, such as science centers and museums.

Image-guidance has been the mainstay for most neurosurgical procedures to aid in accuracy and precision. Developments in visualization tools have brought into existence the current microscope and even sophisticated augmented reality devices providing a human–computer interface. The current microscope poses an ergonomic challenge particularly in scenarios like sitting position. Also, the cost associated with the present microscope hinders the accessibility of micro neurosurgery in most low-to-middle-income countries.

Vision impairments, such as cataracts, affect the visual perception of numerous people worldwide, but are hardly ever considered in architectural or lighting design, due to a lack of suitable tools. In this chapter, we address this issue by presenting a method to simulate vision impairments, in particular cataracts, graphically in virtual reality (VR), for people with normal sight. Such simulations can help train medical personnel, allow relatives of people with vision impairments to better understand the challenges they face in their everyday lives and also help architects and lighting designers to test their designs for accessibility. There have been different approaches and devices used for such simulations in the past. The boom of VR and augmented reality (AR) devices, following the release of the Oculus Rift and HTC Vive headsets, has provided new opportunities to create more immersive and more realistic simulations than ever before. However, the development of a vision impairment simulation is dependent on multiple factors: the designated application area, the impacts of the used hardware on a user’s vision, and of course the impact of the respective vision impairment on different aspects of the human visual system. We will discuss these factors in this chapter and also introduce some basic knowledge on human vision and how to measure it. Then we will illustrate how to simulate vision impairments in VR on the example of cataracts and explain how the presented methodology can be used to calibrate simulated symptoms to the same level of severity for different users. This methodology allows for the first time to conduct quantitative user studies to investigate the impact of certain vision impairments on perception and gain insight that can inform the design process of architects and lighting designers in the future.

3D anatomical medical imaging (CT-scan or MRI) can provide a vision of patient anatomy and pathology. But for any human, even experts, these images have two drawbacks: each voxel density is visualized in grey levels, which are totally inadequate for human eye cones’ perception, and the volume is cut in slices, making any 3D mental representation of the real 3D anatomy of the patient highly complex. Usually, the limits of human perception are overcome by human knowledge. In anatomy, this knowledge is a mix between the average anatomy definition and anatomical variations. But how to understand an anatomical variation from slices in grey levels? In routine, such a difficulty can sometimes be so important that it creates errors. Fortunately, these mistakes can be overcome through 3D patient-specific surgical anatomy. New computer-based medical image analysis and associated 3D modelling provide a highly efficient solution by allowing a patient-specific virtual copy of their anatomic reconstruction. Some articles reporting clinical studies show that up to one-third of initial planning is modified using 3D modelling, and that this modification is always validated efficiently intraoperatively. They also demonstrate that major errors can thus be avoided. In this chapter, we propose to illustrate the 3D modelling process and the associated benefit on a set of patient clinical cases in three main domains: liver surgery, thoracic surgery, and kidney surgery. In each case, we will present the limits of usual medical image analysis due to an average anatomical definition and limited human perception. 3D modelling is provided by the Visible Patient online service and the surgeon then plans his/her surgery on a simple PC using the Visible Patient Planning software. We will then compare the result obtained from a normal anatomical analysis with the result obtained from the 3D modelling and associated preoperative planning. These examples illustrate the great benefit of using patient-specific 3D modelling and preoperative virtual planning in comparison with the usual anatomical definition using only medical image slices. These examples also confirm that this new patient-specific anatomy corrects many mistakes created by the current standard definition, increased by physician interpretation that can vary from one person to another.

Pregnancy is a time of profound anatomical and physiological reorganisation. Understanding these dynamic changes is essential to providing safe and effective maternity care. Traditional teaching methods such as the use of static cadaver specimens are unable to illustrate and give appreciation to the concurrent fetal and maternal changes that occur during this time. This chapter describes the development of the Road to Birth (RtB) a collaborative, multi-modal, digital anatomy program, aimed to provide undergraduate midwifery students with a novel, visual, interactive and accessible, pregnancy education tool. The RtB digital anatomy program provides users with an internal view of pregnancy and fetal development, spanning 0–40 weeks of pregnancy, up to the immediate postpartum period. Users of the program have the opportunity to observe, interact and manipulate detailed 3D models and visualise the growth of a fetus and maternal anatomical changes simultaneously. The program is inclusive of detailed digital fetal and placental models that display both normal and pathological birth positions. The models are accompanied by written educational content that is hypothesised to support both technical and non-technical skill development. The RtB program has been deployed and tested amongst two international cohorts of undergraduate midwifery students. Findings indicate that the RtB as a mobile application and as an immersive virtual reality program have the potential to be useful pregnancy education tools with further empirical testing underway.

We present Anatomy Builder VR and Muscle Action VR that examine how a virtual reality (VR) system can support embodied learning in anatomy education. The backbone of these projects is to pursue an alternative constructivist pedagogical model for learning human and canine anatomy. In Anatomy Builder VR, a user can walk around and examine anatomical models from different perspectives. Direct manipulations in the program allow learners to interact with either individual bones or groups of bones, to determine their viewing orientation and to control the pace of the content manipulation. In Muscle Action VR, a user learns about human muscles and their functions through moving one’s own body in an immersive VR environment, as well as interacting with dynamic anatomy content. Our studies showed that participants enjoyed interactive learning within the VR programs. We suggest applying constructivist methods in VR that support active and experiential learning in anatomy.

Augmented reality applications for anatomy education have seen a large growth in their literature presence as an educational technology. However, the majority of these new anatomy applications limit their educational scope to the labelling of anatomical structures and layers, and simple identification interactions. There is a strong need for expansion of augmented reality applications, in order to give the user more dynamic control of the anatomy material within the application. To meet this need, the mobile augmented reality (AR) application, InNervate AR, was created. This application allows the user to scan a marker for two distinct learning modules; one for labelling and identification of anatomy structures, the other one for interacting with the radial nerve as it relates to the movement of the canine forelimb. A formal user study was run with this new application, which included the Crystal Slicing test for measuring visual-spatial ability, the TOLT test to measure critical thinking ability and both a pre- and post- anatomy knowledge assessment. Data analysis showed a positive qualitative user experience overall, and that the majority of the participants demonstrated an improvement in their anatomical knowledge after using InNervate AR. This implies that the application may prove to be educationally effective. In future, the scope of the application will be expanded, based on this study’s analysis of user data and feedback, and educational modules for all of the motor nerves of the canine forelimb will be developed.