A discrete Reeb graph approach for the segmentation of human body scans

Segmentation of 3D human body (HB) scan is a very challenging problem in applications exploiting human scan data. To tackle this problem, we propose a topological approach based on discrete Reeb graph (DRG) which is an extension of the classical Reeb graph to unorganized cloud of 3D points. The essence of the approach is detecting critical nodes in the DRG thus permitting the extraction of branches that represent the body parts. Because the human body shape representation is built upon global topological features that are preserved so long as the whole structure of the human body does not change, our approach is quite robust against noise, holes, irregular sampling, moderate reference change and posture variation. Experimental results performed on real scan data demonstrate the validity of our method

Nonrigid reconstruction of 3D breast surfaces with a low-cost RGBD camera for surgical planning and aesthetic evaluation

Accounting for 26% of all new cancer cases worldwide, breast cancer remains the most common form of cancer in women. Although early breast cancer has a favourable long-term prognosis, roughly a third of patients suffer from a suboptimal aesthetic outcome despite breast conserving cancer treatment. Clinical-quality 3D modelling of the breast surface therefore assumes an increasingly important role in advancing treatment planning, prediction and evaluation of breast cosmesis. Yet, existing 3D torso scanners are expensive and either infrastructure-heavy or subject to motion artefacts. In this paper we employ a single consumer-grade RGBD camera with an ICP-based registration approach to jointly align all points from a sequence of depth images non-rigidly. Subtle body deformation due to postural sway and respiration is successfully mitigated leading to a higher geometric accuracy through regularised locally affine transformations. We present results from 6 clinical cases where our method compares well with the gold standard and outperforms a previous approach. We show that our method produces better reconstructions qualitatively by visual assessment and quantitatively by consistently obtaining lower landmark error scores and yielding more accurate breast volume estimates

Construction of a human torso model from magnetic resonance images for problems in computational electrocardiography

Journal ArticleApplying mathematical models to real situations often requires the use of discrete geometrical models of the solution domain. In some cases destructive measurement of the objects under examination is acceptable, but in biomedical applications the measurements come from imaging techniques such as X-ray, computer tomography (CT), or magnetic resonance imagining (MRI). A necessary early step in the modeling process is then to extract from these images the measurements (locations and distances) that form the basis of the geometrical model. In this paper we describe the construction of a geometrical model of the human thorax based on the high resolution MRI scan of a single subject. We outline the scanning procedure, the image collection and conversion to computerized image files, the segmentation of the images into boundary nodes, and the connection of these nodes into surface, and then volume, meshes. Included are brief descriptions of the tools developed at the CVRTI for this project, as well as our experiences in creating and using them. The result of this work was a pair of models at two different levels of spatial resolution, which set new standards in the area of bioelectric field modeling and the application of these models has been described previously [1, 2]

Respiratory monitoring using fibre long period grating sensors

We demonstrate the use of a series of in-line fibre long period grating curvature sensors on a garment, used to monitor the thoracic and abdominal volumetric tidal movements of a human subject. These results are used to obtain volumetric tidal changes of the human torso showing reasonable agreement with a spirometer used simultaneously to record the volume at the mouth during breathing. The curvature sensors are based upon long period gratings written in a progressive three layered fibre that are insensitive to refractive index changes. The sensor platform consists of the long period grating laid upon a carbon fibre ribbon, which is encapsulated in a low temperature curing silicone rubber

3D Human Pose Estimation from Deep Multi-View 2D Pose

Human pose estimation - the process of recognizing a human's limb positions and orientations in a video - has many important applications including surveillance, diagnosis of movement disorders, and computer animation. While deep learning has lead to great advances in 2D and 3D pose estimation from single video sources, the problem of estimating 3D human pose from multiple video sensors with overlapping fields of view has received less attention. When the application allows use of multiple cameras, 3D human pose estimates may be greatly improved through fusion of multi-view pose estimates and observation of limbs that are fully or partially occluded in some views. Past approaches to multi-view 3D pose estimation have used probabilistic graphical models to reason over constraints, including per-image pose estimates, temporal smoothness, and limb length. In this paper, we present a pipeline for multi-view 3D pose estimation of multiple individuals which combines a state-of-art 2D pose detector with a factor graph of 3D limb constraints optimized with belief propagation. We evaluate our results on the TUM-Campus and Shelf datasets for multi-person 3D pose estimation and show that our system significantly out-performs the previous state-of-the-art with a simpler model of limb dependency

Multimodal image registration of the scoliotic torso for surgical planning

Background This paper presents a method that registers MRIs acquired in prone position, with surface topography (TP) and X-ray reconstructions acquired in standing position, in order to obtain a 3D representation of a human torso incorporating the external surface, bone structures, and soft tissues. Methods TP and X-ray data are registered using landmarks. Bone structures are used to register each MRI slice using an articulated model, and the soft tissue is confined to the volume delimited by the trunk and bone surfaces using a constrained thin-plate spline. Results The method is tested on 3 pre-surgical patients with scoliosis and shows a significant improvement, qualitatively and using the Dice similarity coefficient, in fitting the MRI into the standing patient model when compared to rigid and articulated model registration. The determinant of the Jacobian of the registration deformation shows higher variations in the deformation in areas closer to the surface of the torso. Conclusions The novel, resulting 3D full torso model can provide a more complete representation of patient geometry to be incorporated in surgical simulators under development that aim at predicting the effect of scoliosis surgery on the external appearance of the patient’s torso.Canadian Institute for Health and Research (CIHR

Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies

We present a unified deformation model for the markerless capture of multiple scales of human movement, including facial expressions, body motion, and hand gestures. An initial model is generated by locally stitching together models of the individual parts of the human body, which we refer to as the "Frankenstein" model. This model enables the full expression of part movements, including face and hands by a single seamless model. Using a large-scale capture of people wearing everyday clothes, we optimize the Frankenstein model to create "Adam". Adam is a calibrated model that shares the same skeleton hierarchy as the initial model but can express hair and clothing geometry, making it directly usable for fitting people as they normally appear in everyday life. Finally, we demonstrate the use of these models for total motion tracking, simultaneously capturing the large-scale body movements and the subtle face and hand motion of a social group of people

A Developmental Organization for Robot Behavior

This paper focuses on exploring how learning and development can be structured in synthetic (robot) systems. We present a developmental assembler for constructing reusable and temporally extended actions in a sequence. The discussion adopts the traditions of dynamic pattern theory in which behavior is an artifact of coupled dynamical systems with a number of controllable degrees of freedom. In our model, the events that delineate control decisions are derived from the pattern of (dis)equilibria on a working subset of sensorimotor policies. We show how this architecture can be used to accomplish sequential knowledge gathering and representation tasks and provide examples of the kind of developmental milestones that this approach has already produced in our lab

Undergraduate Research Forum

The Undergraduate Research Forum highlights the valued tradition at St. Norbert College of collaboration taking place in laboratories, studios, and other scholarly or creative settings between our students and our faculty and staff, resulting in a rich array of scholarly research and creative work. This celebration features projects that evolved out of independent studies, directed research, class assignments, and casual interactions as well as formal collaborations supported by internal and external grant fundin

Using QFD As A Method To Develop Functional Medical Products For Children With Cancer.

Quality Function Deployment (QFD) is a recognised method of translating customer needs into appropriate technical requirements to inform ergonomic design development. This paper details how QFD has been used to develop a tactile advanced product for a medical application. The project has undertaken innovative experimental and industrial research which has led to the design of a child-focused “Wiggle Bag” which will be used to safely harness and reduce infection at the site of a venous catheter placed in the chest wall of long-term child cancer sufferers. Children with cancer regularly have long term central venous catheters inserted through their upper chest wall to deliver medication. They can result in medical issues, particularly infections or accidental removal, but also discomfort for the children, particularly when sleeping. The research uses an inductive approach, triangulating various research strategies including questionnaires, focus groups and interviews from parents, carers and medical personnel. QFD was used to bring together the key findings from the primary data analysis to establish design criteria and inform the product development. The outcome of the research was a functional product ergonomically designed for maximum comfort and safety, with the added unique selling point of having antibacterial properties