Semi-automatic 3D Segmentation Of Costal Cartilage In CT Data From Pectus Excavatum Patients

One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.

A-scan ultrasound system for real-time puncture safety assessment during percutaneous nephrolithotomy

Background: Kidney stone is a major universal health problem, affecting 10% of the population worldwide. Percutaneous nephrolithotomy is a first-line and established procedure for disintegration and removal of renal stones. Its surgical success depends on the precise needle puncture of renal calyces, which remains the most challenging task for surgeons. This work describes and tests a new ultrasound based system to alert the surgeon when undesirable anatomical structures are in between the puncture path defined through a tracked needle. Methods: Two circular ultrasound transducers were built with a single 3.3-MHz piezoelectric ceramic PZT SN8, 25.4 mm of radius and resin-epoxy matching and backing layers. One matching layer was designed with a concave curvature to work as an acoustic lens with long focusing. The A-scan signals were filtered and processed to automatically detect reflected echoes. Results: The transducers were mapped in water tank and tested in a study involving 45 phantoms. Each phantom mimics different needle insertion trajectories with a percutaneous path length between 80 and 150 mm. Results showed that the beam cross-sectional area oscillates around the ceramics radius and it was possible to automatically detect echo signals in phantoms with length higher than 80 mm. Conclusions: This new solution may alert the surgeon about anatomical tissues changes during needle insertion, which may decrease the need of X-Ray radiation exposure and ultrasound image evaluation during percutaneous puncture.

Validation of percutaneous puncture trajectory during renal access using 4D ultrasound reconstruction

Background: An accurate percutaneous puncture is essential for disintegration and removal of renal stones. Although this procedure has proven to be safe, some organs surrounding the renal target might be accidentally perforated. This work describes a new intraoperative framework where tracked surgical tools are superimposed within 4D ultrasound imaging for security assessment of the percutaneous puncture trajectory (PPT). Methods: A PPT is first generated from the skin puncture site towards an anatomical target, using the information retrieved by electromagnetic motion tracking sensors coupled to surgical tools. Then, 2D ultrasound images acquired with a tracked probe are used to reconstruct a 4D ultrasound around the PPT under GPU processing. Volume hole-filling was performed in different processing time intervals by a tri-linear interpolation method. At spaced time intervals, the volume of the anatomical structures was segmented to ascertain if any vital structure is in between PPT and might compromise the surgical success. To enhance the volume visualization of the reconstructed structures, different render transfer functions were used. Results: Real-time US volume reconstruction and rendering with more than 25 frames/s was only possible when rendering only three orthogonal slice views. When using the whole reconstructed volume one achieved 8-15 frames/s. 3 frames/s were reached when one introduce the segmentation and detection if some structure intersected the PPT. Conclusions: The proposed framework creates a virtual and intuitive platform that can be used to identify and validate a PPT to safely and accurately perform the puncture in percutaneous nephrolithotomy.

Computer-aided recognition of dental implants in X-ray images

Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.

IDEA MANAGEMENT SYSTEM - AN ESSENTIAL COMPONENT IN THE CONTINUOUS IMPROVEMENT OF QUALITY AND INNOVATION

It is known the power of ideas is tremendous. But there are employees in many companies who have good ideas but not put them into practice. On the other hand, there are many others who have good ideas and are encouraged to contribute their ideas for innovation in the company. This study attempts to identify factors that contribute to success in managing ideas and consequent business innovation. The method used was the case study applied to two companies. During the investigation, factors considered essential for the success of an idea management program were identified, of which we highlight, among others, evidences the results, involvement of the top management, establishment of goals and objectives; recognition; dissemination of good results. Companies with these implemented systems, capture the best ideas from their collaborators and apply them internally. This study intends to contribute to business innovation in enterprises through creation and idea management, mainly through collecting the best ideas of their own employees. The results of this study can be used to help improving deployed suggestions systems, as well as, all managers who wish to implement suggestions systems/ideas management systems.

Assessment of Laparoscopic Skills Performance: 2D Versus 3D Vision and Classic Instrument Versus New Hand-Held Robotic Device for Laparoscopy

Introduction and Objectives. Laparoscopic surgery has undeniable advantages, such as reduced postoperative pain, smaller incisions, and faster recovery. However, to improve surgeons’ performance, ergonomic adaptations of the laparoscopic instruments and introduction of robotic technology are needed. The aim of this study was to ascertain the influence of a new hand-held robotic device for laparoscopy (HHRDL) and 3D vision on laparoscopic skills performance of 2 different groups, naïve and expert. Materials and Methods. Each participant performed 3 laparoscopic tasks—Peg transfer, Wire chaser, Knot—in 4 different ways. With random sequencing we assigned the execution order of the tasks based on the first type of visualization and laparoscopic instrument. Time to complete each laparoscopic task was recorded and analyzed with one-way analysis of variance. Results. Eleven experts and 15 naïve participants were included. Three-dimensional video helps the naïve group to get better performance in Peg transfer, Wire chaser 2 hands, and Knot; the new device improved the execution of all laparoscopic tasks (P < .05). For expert group, the 3D video system benefited them in Peg transfer and Wire chaser 1 hand, and the robotic device in Peg transfer, Wire chaser 1 hand, and Wire chaser 2 hands (P < .05). Conclusion. The HHRDL helps the execution of difficult laparoscopic tasks, such as Knot, in the naïve group. Three-dimensional vision makes the laparoscopic performance of the participants without laparoscopic experience easier, unlike those with experience in laparoscopic procedures.