3D Face Reconstruction from 2D Pictures: First Results of a Web-Based Computer Aided System for Aesthetic Procedures

The human face is a vital component of our identity and many people undergo medical aesthetics procedures in order to achieve an ideal or desired look. However, communication between physician and patient is fundamental to understand the patient’s wishes and to achieve the desired results. To date, most plastic surgeons rely on either “free hand” 2D drawings on picture printouts or computerized picture morphing. Alternatively, hardware dependent solutions allow facial shapes to be created and planned in 3D, but they are usually expensive or complex to handle. To offer a simple and hardware independent solution, we propose a web-based application that uses 3 standard 2D pictures to create a 3D representation of the patient’s face on which facial aesthetic procedures such as filling, skin clearing or rejuvenation, and rhinoplasty are planned in 3D. The proposed application couples a set of well-established methods together in a novel manner to optimize 3D reconstructions for clinical use. Face reconstructions performed with the application were evaluated by two plastic surgeons and also compared to ground truth data. Results showed the application can provide accurate 3D face representations to be used in clinics (within an average of 2 mm error) in less than 5 min.

Mechanisms of Ligand–Protein Interaction in Sec-14-like Transporters Investigated by Computer Simulations

We review our recent work on protein-ligand interactions in vitamin transporters of the Sec-14-like protein. Our studies focused on the cellular-retinaldehyde binding protein (CRALBP) and the alpha-tocopherol transfer protein (alpha-TTP). CRALBP is responsible for mobilisation and photo-protection of short-chain cis-retinoids in the dim-light visual cycle or rod photoreceptors. alpha-TTP is a key protein responsible for selection and retention of RRR-alpha-tocopherol, the most active isoform of vitamin E in superior animals. Our simulation studies evidence how subtle chemical variations in the substrate can lead to significant distortion in the structure of the complex, and how these changes can either lead to new protein function, or be used to model engineered protein variants with tailored properties. Finally, we show how integration of computational and experimental results can contribute in synergy to the understanding of fundamental processes at the biomolecular scale.

Computer assisted planning and navigation of periacetabular osteotomy with range of motion optimization

Femoroacetabular impingement (FAI) before or after Periacetabular Osteotomy (PAO) is surprisingly frequent and surgeons need to be aware of the risk preoperatively and be able to avoid it intraoperatively. In this paper we present a novel computer assisted planning and navigation system for PAO with impingement analysis and range of motion (ROM) optimization. Our system starts with a fully automatic detection of the acetabular rim, which allows for quantifying the acetabular morphology with parameters such as acetabular version, inclination and femoral head coverage ratio for a computer assisted diagnosis and planning. The planned situation was optimized with impingement simulation by balancing acetabuar coverage with ROM. Intra-operatively navigation was conducted until the optimized planning situation was achieved. Our experimental results demonstrated: 1) The fully automated acetabular rim detection was validated with accuracy 1.1 ± 0.7mm; 2) The optimized PAO planning improved ROM significantly compared to that without ROM optimization; 3) By comparing the pre-operatively planned situation and the intra-operatively achieved situation, sub-degree accuracy was achieved for all directions.

Fully Automatic CT Segmentation for Computer-Assisted Pre-operative Planning of Hip Arthroscopy

Extraction of both pelvic and femoral surface models of a hip joint from CT data for computer-assisted pre-operative planning of hip arthroscopy is addressed. We present a method for a fully automatic image segmentation of a hip joint. Our method works by combining fast random forest (RF) regression based landmark detection, atlas-based segmentation, with articulated statistical shape model (aSSM) based hip joint reconstruction. The two fundamental contributions of our method are: (1) An improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the atlas-based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Validation on 30 hip CT images show that our method achieves high performance in segmenting pelvis, left proximal femur, and right proximal femur surfaces with an average accuracy of 0.59 mm, 0.62 mm, and 0.58 mm, respectively.

Virtobot--a multi-functional robotic system for 3D surface scanning and automatic post mortem biopsy

The Virtopsy project, a multi-disciplinary project that involves forensic science, diagnostic imaging, computer science, automation technology, telematics and biomechanics, aims to develop new techniques to improve the outcome of forensic investigations. This paper presents a new approach in the field of minimally invasive virtual autopsy for a versatile robotic system that is able to perform three-dimensional (3D) surface scans as well as post mortem image-guided soft tissue biopsies.

Anatomically-Driven Soft-Tissue Simulation Strategy for Cranio-Maxillofacial Surgery Using Facial Muscle Template Model

We propose a computationally efficient and biomechanically relevant soft-tissue simulation method for cranio-maxillofacial (CMF) surgery. A template-based facial muscle reconstruction was introduced to minimize the efforts on preparing a patient-specific model. A transversely isotropic mass-tensor model (MTM) was adopted to realize the effect of directional property of facial muscles in reasonable computation time. Additionally, sliding contact around teeth and mucosa was considered for more realistic simulation. Retrospective validation study with postoperative scan of a real patient showed that there were considerable improvements in simulation accuracy by incorporating template-based facial muscle anatomy and sliding contact.

Determination of Pelvic Orientation from Ultrasound Images Using Patch-SSMs and a Hierarchical Speed of Sound Compensation Strategy

In the field of computer assisted orthopedic surgery (CAOS) the anterior pelvic plane (APP) is a common concept to determine the pelvic orientation by digitizing distinct pelvic landmarks. As percutaneous palpation is - especially for obese patients - known to be error-prone, B-mode ultrasound (US) imaging could provide an alternative means. Several concepts of using ultrasound imaging to determine the APP landmarks have been introduced. In this paper we present a novel technique, which uses local patch statistical shape models (SSMs) and a hierarchical speed of sound compensation strategy for an accurate determination of the APP. These patches are independently matched and instantiated with respect to associated point clouds derived from the acquired ultrasound images. Potential inaccuracies due to the assumption of a constant speed of sound are compensated by an extended reconstruction scheme. We validated our method with in-vitro studies using a plastic bone covered with a soft-tissue simulation phantom and with a preliminary cadaver trial.

Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.