A navigation system for open liver surgery: design, workflow and first clinical applications

The surgical treatment of liver tumours relies on precise localization of the lesions and detailed knowledge of the patient-specific vascular and biliary anatomy. Detailed three-dimensional (3D) anatomical information facilitates complete tumour removal while preserving a sufficient amount of functional liver tissue.

Computer-assisted liver surgery: clinical applications and technological trends

Oncological liver surgery and interventions aim for removal of tumor tissue while preserving a sufficient amount of functional tissue to ensure organ regeneration. This requires detailed understanding of the patient-specific internal organ anatomy (blood vessel system, bile ducts, tumor location). The introduction of computer support in the surgical process enhances anatomical orientation through patient-specific 3D visualization and enables precise reproduction of planned surgical strategies though stereotactic navigation technology. This article provides clinical background information on indications and techniques for the treatment of liver tumors, reviews the technological contributions addressing the problem of organ motion during navigated surgery on a deforming organ, and finally presents an overview of the clinical experience in computer-assisted liver surgery and interventions. The review concludes that several clinically applicable solutions for computer aided liver surgery are available and small-scale clinical trials have been performed. Further developments will be required more accurate and faster handling of organ deformation and large clinical studies will be required for demonstrating the benefits of computer aided liver surgery.

Landmark-based augmented reality system for paranasal and transnasal endoscopic surgeries

BACKGROUND: In this paper we present a landmark-based augmented reality (AR) endoscope system for endoscopic paranasal and transnasal surgeries along with fast and automatic calibration and registration procedures for the endoscope. METHODS: Preoperatively the surgeon selects natural landmarks or can define new landmarks in CT volume. These landmarks are overlaid, after proper registration of preoperative CT to the patient, on the endoscopic video stream. The specified name of the landmark, along with selected colour and its distance from the endoscope tip, is also augmented. The endoscope optics are calibrated and registered by fast and automatic methods. Accuracy of the system is evaluated in a metallic grid and cadaver set-up. RESULTS: Root mean square (RMS) error of the system is 0.8 mm in a controlled laboratory set-up (metallic grid) and was 2.25 mm during cadaver studies. CONCLUSIONS: A novel landmark-based AR endoscope system is implemented and its accuracy is evaluated. Augmented landmarks will help the surgeon to orientate and navigate the surgical field. Studies prove the capability of the system for the proposed application. Further clinical studies are planned in near future.

3D Conversion using Vanishing Points and Image Warping

We describe a user assisted technique for 3D stereo conversion from 2D images. Our approach exploits the geometric structure of perspective images including vanishing points. We allow a user to indicate lines, planes, and vanishing points in the input image, and directly employ these as constraints in an image warping framework to produce a stereo pair. By sidestepping explicit construction of a depth map, our approach is applicable to more general scenes and avoids potential artifacts of depth-image-based rendering. Our method is most suitable for scenes with large scale structures such as buildings.

Comparison of freehand-navigated and aiming device-navigated targeting of liver lesions

BACKGROUND Accurate needle placement is crucial for the success of percutaneous radiological needle interventions. We compared three guiding methods using an optical-based navigation system: freehand, using a stereotactic aiming device and active depth control, and using a stereotactic aiming device and passive depth control. METHODS For each method, 25 punctures were performed on a non-rigid phantom. Five 1 mm metal screws were used as targets. Time requirements were recorded, and target positioning errors (TPE) were measured on control scans as the distance between needle tip and target. RESULTS Time requirements were reduced using the aiming device and passive depth control. The Euclidian TPE was similar for each method (4.6 ± 1.2-4.9 ± 1.7 mm). However, the lateral component was significantly lower when an aiming device was used (2.3 ± 1.3-2.8 ± 1.6 mm with an aiming device vs 4.2 ± 2.0 mm without). DISCUSSION Using an aiming device may increase the lateral accuracy of navigated needle insertion.

A Closed-Form, Consistent and Robust Solution to Uncalibrated Photometric Stereo Via Local Diffuse Reflectance Maxima

Images of an object under different illumination are known to provide strong cues about the object surface. A mathematical formalization of how to recover the normal map of such a surface leads to the so-called uncalibrated photometric stereo problem. In the simplest instance, this problem can be reduced to the task of identifying only three parameters: the so-called generalized bas-relief (GBR) ambiguity. The challenge is to find additional general assumptions about the object, that identify these parameters uniquely. Current approaches are not consistent, i.e., they provide different solutions when run multiple times on the same data. To address this limitation, we propose exploiting local diffuse reflectance (LDR) maxima, i.e., points in the scene where the normal vector is parallel to the illumination direction (see Fig. 1). We demonstrate several noteworthy properties of these maxima: a closed-form solution, computational efficiency and GBR consistency. An LDR maximum yields a simple closed-form solution corresponding to a semi-circle in the GBR parameters space (see Fig. 2); because as few as two diffuse maxima in different images identify a unique solution, the identification of the GBR parameters can be achieved very efficiently; finally, the algorithm is consistent as it always returns the same solution given the same data. Our algorithm is also remarkably robust: It can obtain an accurate estimate of the GBR parameters even with extremely high levels of outliers in the detected maxima (up to 80 % of the observations). The method is validated on real data and achieves state-of-the-art results.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

A complete-pelvis segmentation framework for image-free total hip arthroplasty (THA): methodology and clinical study

Background Complete-pelvis segmentation in antero-posterior pelvic radiographs is required to create a patient-specific three-dimensional pelvis model for surgical planning and postoperative assessment in image-free navigation of total hip arthroplasty. Methods A fast and robust framework for accurately segmenting the complete pelvis is presented, consisting of two consecutive modules. In the first module, a three-stage method was developed to delineate the left hemipelvis based on statistical appearance and shape models. To handle complex pelvic structures, anatomy-specific information processing techniques were employed. As the input to the second module, the delineated left hemi-pelvis was then reflected about an estimated symmetry line of the radiograph to initialize the right hemi-pelvis segmentation. The right hemi-pelvis was segmented by the same three-stage method, Results Two experiments conducted on respectively 143 and 40 AP radiographs demonstrated a mean segmentation accuracy of 1.61±0.68 mm. A clinical study to investigate the postoperative assessment of acetabular cup orientations based on the proposed framework revealed an average accuracy of 1.2°±0.9° and 1.6°±1.4° for anteversion and inclination, respectively. Delineation of each radiograph costs less than one minute. Conclusions Despite further validation needed, the preliminary results implied the underlying clinical applicability of the proposed framework for image-free THA.

Dish Detection and Segmentation for Dietary Assessment on Smartphones

Diet-related chronic diseases severely affect personal and global health. However, managing or treating these diseases currently requires long training and high personal involvement to succeed. Computer vision systems could assist with the assessment of diet by detecting and recognizing different foods and their portions in images. We propose novel methods for detecting a dish in an image and segmenting its contents with and without user interaction. All methods were evaluated on a database of over 1600 manually annotated images. The dish detection scored an average of 99% accuracy with a .2s/image run time, while the automatic and semi-automatic dish segmentation methods reached average accuracies of 88% and 91% respectively, with an average run time of .5s/image, outperforming competing solutions.

Numerical model of the human cornea based on stromal microstructure: identification of mechanical properties for two age groups

The optical quality of the human eye mainly depends on the refractive performance of the cornea. The shape of the cornea is a mechanical balance between intraocular pressure and tissue intrinsic stiffness. Several surgical procedures in ophthalmology alter the biomechanics of the cornea to provoke local or global curvature changes for vision correction. Legitimated by the large number of surgical interventions performed every day, the demand for a deeper understanding of corneal biomechanics is rising to improve the safety of procedures and medical devices. The aim of our work is to propose a numerical model of corneal biomechanics, based on the stromal microstructure. Our novel anisotropic constitutive material law features a probabilistic weighting approach to model collagen fiber distribution as observed on human cornea by Xray scattering analysis (Aghamohammadzadeh et. al., Structure, February 2004). Furthermore, collagen cross-linking was explicitly included in the strain energy function. Results showed that the proposed model is able to successfully reproduce both inflation and extensiometry experimental data (Elsheikh et. al., Curr Eye Res, 2007; Elsheikh et. al., Exp Eye Res, May 2008). In addition, the mechanical properties calculated for patients of different age groups (Group A: 65-79 years; Group B: 80-95 years) demonstrate an increased collagen cross-linking, and a decrease in collagen fiber elasticity from younger to older specimen. These findings correspond to what is known about maturing fibrous biological tissue. Since the presented model can handle different loading situations and includes the anisotropic distribution of collagen fibers, it has the potential to simulate clinical procedures involving nonsymmetrical tissue interventions. In the future, such mechanical model can be used to improve surgical planning and the design of next generation ophthalmic devices.