Low-profile titanium mesh in the use of orbital reconstruction: A pilot study

The purpose of this study was to share our clinical experience in the use and accuracy of a newly designed, low-profile titanium mesh (Modus OPS 1.5; Medartis, Basel, Switzerland) for primary internal orbital reconstruction.

[Laparoscopic management of genital prolapse by lateral suspension using mesh: a series of 377 patients]

Genital prolapse is frequent and can be found in about 50% of parous women. Its etiology is complex and multifactorial. Predisposing factors include: genetics (connective tissue disorders, family history); general state (age, parity, weight, smoking, obstructive pulmonary disease); trauma (carrying heavy loads, intense physical exercise); or iatrogenic (post hysterectomy). Treatment can be conservative or surgical and depends mainly on the severity of symptoms. Developments in surgical techniques and synthetic material in the last 20 years enabled us to use minimally invasive procedures with improved post operative course and decreased recurrence rates.

Prospective randomized trial comparing sutured with sutureless mesh fixation for Lichtenstein hernia repair: long-term results

Following Lichtenstein hernia repair, up to 25% of patients experience prolonged postoperative and chronic pain as well as discomfort in the groin. One of the underlying causes of these complaints are the compression or irritation of nerves by the sutures used to fixate the mesh. We compared the level and rate of chronic pain in patients operated with the classical Lichtenstein technique fixated by sutures to patients with sutureless mesh fixation technique.

ADAM: Administration and Deployment of Adhoc Mesh Networks

Costly on-site node repairs in wireless mesh networks (WMNs) can be required due to misconfiguration, corrupt software updates, or unavailability during updates. We propose ADAM as a novel management framework that guarantees accessibility of individual nodes in these situations. ADAM uses a decentralised distribution mechanism and self-healing mechanisms for safe configuration and software updates. In order to implement the ADAM management and self-healing mechanisms, an easy-to-learn and extendable build system for a small footprint embedded Linux distribution for WMNs has been developed. The paper presents the ADAM concept, the build system for the Linux distribution and the management architecture.

Pathology hinting as the combination of automatic segmentation with a statistical shape model

With improvements in acquisition speed and quality, the amount of medical image data to be screened by clinicians is starting to become challenging in the daily clinical practice. To quickly visualize and find abnormalities in medical images, we propose a new method combining segmentation algorithms with statistical shape models. A statistical shape model built from a healthy population will have a close fit in healthy regions. The model will however not fit to morphological abnormalities often present in the areas of pathologies. Using the residual fitting error of the statistical shape model, pathologies can be visualized very quickly. This idea is applied to finding drusen in the retinal pigment epithelium (RPE) of optical coherence tomography (OCT) volumes. A segmentation technique able to accurately segment drusen in patients with age-related macular degeneration (AMD) is applied. The segmentation is then analyzed with a statistical shape model to visualize potentially pathological areas. An extensive evaluation is performed to validate the segmentation algorithm, as well as the quality and sensitivity of the hinting system. Most of the drusen with a height of 85.5 microm were detected, and all drusen at least 93.6 microm high were detected.

Graph-Based Multi-Surface Segmentation of OCT Data Using Trained Hard and Soft Constraints

Optical coherence tomography (OCT) is a well-established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graph-based multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ±0.54 μm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.

Intraperitoneal mesh implantation for fascial dehiscence and open abdomen

Postoperative fascial dehiscence and open abdomen are severe postoperative complications and are associated with surgical site infections, fistula, and hernia formation at long-term follow-up. This study was designed to investigate whether intraperitoneal implantation of a composite prosthetic mesh is feasible and safe.