True-color 3D rendering of human anatomy using surface-guided color sampling from cadaver cryosection image data: A practical approach Jon Jatsu Azkue

Three-dimensional computer graphics are increasingly used for scientific visualization and for communicating anatomical knowledge and data. This study presents a practical method to produce true-color 3D surface renditions of anatomical structures. The procedure involves extracting the surface geometry of the structure of interest from a stack of cadaver cryosection images, using the extracted surface as a probe to retrieve color information from cryosection data, and mapping sampled colors back onto the surface model to produce a true-color rendition. Organs and body parts can be rendered separately or in combination to create custom anatomical scenes. By editing the surface probe, structures of interest can be rendered as if they had been previously dissected or prepared for anatomical demonstration. The procedure is highly flexible and nondestructive, offering new opportunities to present and communicate anatomical information and knowledge in a visually realistic manner. The technical procedure is described, including freely available open-source software tools involved in the production process, and examples of color surface renderings of anatomical structures are provided

RGBD Datasets: Past, Present and Future

Since the launch of the Microsoft Kinect, scores of RGBD datasets have been released. These have propelled advances in areas from reconstruction to gesture recognition. In this paper we explore the field, reviewing datasets across eight categories: semantics, object pose estimation, camera tracking, scene reconstruction, object tracking, human actions, faces and identification. By extracting relevant information in each category we help researchers to find appropriate data for their needs, and we consider which datasets have succeeded in driving computer vision forward and why. Finally, we examine the future of RGBD datasets. We identify key areas which are currently underexplored, and suggest that future directions may include synthetic data and dense reconstructions of static and dynamic scenes.Comment: 8 pages excluding references (CVPR style

Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

In this paper, we propose a generative framework that unifies depth-based 3D facial pose tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy occlusions and arbitrary facial expression variations. Specifically, we introduce a statistical 3D morphable model that flexibly describes the distribution of points on the surface of the face model, with an efficient switchable online adaptation that gradually captures the identity of the tracked subject and rapidly constructs a suitable face model when the subject changes. Moreover, unlike prior art that employed ICP-based facial pose estimation, to improve robustness to occlusions, we propose a ray visibility constraint that regularizes the pose based on the face model's visibility with respect to the input point cloud. Ablation studies and experimental results on Biwi and ICT-3DHP datasets demonstrate that the proposed framework is effective and outperforms completing state-of-the-art depth-based methods

Three-dimensional anatomical atlas of the human body

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsAnatomical atlases allow mapping the anatomical structures of the human body. Early versions of these systems consisted of analogic representations with informative text and labelled images of the human body. With the advent of computer systems, digital versions emerged and the third dimension was introduced. Consequently, these systems increased their efficiency, allowing more realistic visualizations with improved interactivity. The development of anatomical atlases in geographic information systems (GIS) environments allows the development of platforms with a high degree of interactivity and with tools to explore and analyze the human body. In this thesis, a prototype for the human body representation is developed. The system includes a 3D GIS topological model, a graphical user interface and functions to explore and analyze the interior and the surface of the anatomical structures of the human body. The GIS approach relies essentially on the topological characteristics of the model and on the kind of available functions, which include measurement, identification, selection and analysis. With the incorporation of these functions, the final system has the ability to replicate the kind of information provided by the conventional anatomical atlases and also provides a higher level of functionality, since some of the atlases limitations are precisely features offered by GIS, namely, interactive capabilities, multilayer management, measurement tools, edition mode, allowing the expansion of the information contained in the system, and spatial analyzes

A Novel Method of Anatomical Data Acquisition Using the Perceptron ScanWorks V5 Scanner

A drastic reduction in the time available for cadaveric dissection and anatomy teaching in medical and surgical education has increased the requirement to supplement learning with the use of virtual gross anatomy training tools. In light of this, a number of known studies have approached the task of sourcing anatomical data from cadaveric material for end us in creating 3D reconstructions of the human body by producing vast image libraries of anatomical cross sections. However, the processing involved in the conversion of cross sectional images to reconstructions in 3D elicits a number of problems in creating an accurate and adequately detailed end product, suitable for educational. In this paperwe have employed a unique approach in a pilot study acquire anatomical data for end-use in 3D anatomical reconstruction by using topographical 3D laser scanning and high-resolution digital photography of all clinically relevant structures from the lower limb of a male cadaveric specimen. As a result a comprehensive high-resolution dataset, comprising 3D laser scanned data and corresponding colour photography was obtained from all clinically relevant gross anatomical structures associated with the male lower limb. This unique dataset allows a very unique and novel way to capture anatomical data and saves on the laborious processing of image segmentation common to conventional image acquisition used clinically, like CT and MRI scans. From this, it provides a dataset which can then be used across a number of commercial products dependent on the end-users requirements for development of computer training packages in medical and surgical rehearsal

A Novel Method of Anatomical Data Acquisition Using the Perceptron ScanWorks V5 Scanner

A drastic reduction in the time available for cadaveric dissection and anatomy teaching in medical and surgical education has increased the requirement to supplement learning with the use of virtual gross anatomy training tools. In light of this, a number of known studies have approached the task of sourcing anatomical data from cadaveric material for end us in creating 3D reconstructions of the human body by producing vast image libraries of anatomical cross sections. However, the processing involved in the conversion of cross sectional images to reconstructions in 3D elicits a number of problems in creating an accurate and adequately detailed end product, suitable for educational. In this paperwe have employed a unique approach in a pilot study acquire anatomical data for end-use in 3D anatomical reconstruction by using topographical 3D laser scanning and high-resolution digital photography of all clinically relevant structures from the lower limb of a male cadaveric specimen. As a result a comprehensive high-resolution dataset, comprising 3D laser scanned data and corresponding colour photography was obtained from all clinically relevant gross anatomical structures associated with the male lower limb. This unique dataset allows a very unique and novel way to capture anatomical data and saves on the laborious processing of image segmentation common to conventional image acquisition used clinically, like CT and MRI scans. From this, it provides a dataset which can then be used across a number of commercial products dependent on the end-users requirements for development of computer training packages in medical and surgical rehearsal

RGB-D based framework to Acquire, Visualize and Measure the Human Body for Dietetic Treatments

This research aims to improve dietetic-nutritional treatment using state-of-the-art RGB-D sensors and virtual reality (VR) technology. Recent studies show that adherence to treatment can be improved using multimedia technologies. However, there are few studies using 3D data and VR technologies for this purpose. On the other hand, obtaining 3D measurements of the human body and analyzing them over time (4D) in patients undergoing dietary treatment is a challenging field. The main contribution of the work is to provide a framework to study the effect of 4D body model visualization on adherence to obesity treatment. The system can obtain a complete 3D model of a body using low-cost technology, allowing future straightforward transference with sufficient accuracy and realistic visualization, enabling the analysis of the evolution (4D) of the shape during the treatment of obesity. The 3D body models will be used for studying the effect of visualization on adherence to obesity treatment using 2D and VR devices. Moreover, we will use the acquired 3D models to obtain measurements of the body. An analysis of the accuracy of the proposed methods for obtaining measurements with both synthetic and real objects has been carried out