Predictors of Risk and Success of Obesity Surgery.

Background: Obesity surgery has proven successful for weight loss and the resolution of comorbidities. There is, however, little evidence on its success and the risk of complications when considering age of onset of obesity (AOO), years of obesity (YOO), preoperative body mass index (BMI), Edmonton obesity staging system (EOSS) score, and age as possible predictors of weight loss, the resolution of comorbidities, and the risk of complications.

Methods: Patients who underwent Roux-en-Y gastric bypass (RYGB) and laparoscopic sleeve gastrectomy (LSG) from a prospective database were analyzed.

Is there a Reason Why Obese Patients Choose Either Conservative Treatment or Surgery?

Background: The effects of bariatric surgery on excess weight loss (EWL) and comorbidities are proven. Still, a significant number of patients prefer conservative therapy (ConsP).

Objectives: The goal of this study was to examine why ConsP and patients awaiting bariatric surgery (SurgP) choose which therapy, and to define the differences in their expectations.

Bridging the gap between formal and experience-based knowledge for context-aware laparoscopy.

Purpose: Computer assistance is increasingly common in surgery. However, the amount of information is bound to overload processing abilities of surgeons. We propose methods to recognize the current phase of a surgery for context-aware information filtering.

Toward cognitive pipelines of medical assistance algorithms.

Purpose: Assistance algorithms for medical tasks have great potential to support physicians with their daily work. However, medicine is also one of the most demanding domains for computer-based support systems, since medical assistance tasks are complex and the practical experience of the physician is crucial. Recent developments in the area of cognitive computing appear to be well suited to tackle medicine as an application domain.

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition.

Purpose: The rise of intraoperative information threatens to outpace our abilities to process it. Context-aware systems, filtering information to automatically adapt to the current needs of the surgeon, are necessary to fully profit from computerized surgery. To attain context awareness, representation of medical knowledge is crucial.

Crowdtruth validation: a new paradigm for validating algorithms that rely on image correspondences.

Purpose: Feature tracking and 3D surface reconstruction are key enabling techniques to computer-assisted minimally invasive surgery. One of the major bottlenecks related to training and validation of new algorithms is the lack of large amounts of annotated images that fully capture the wide range of anatomical/scene variance in clinical practice. To address this issue, we propose a novel approach to obtaining large numbers of high-quality reference image annotations at low cost in an extremely short period of time.

Crowdsourcing for reference correspondence generation in endoscopic images.

Computer-assisted minimally-invasive surgery (MIS) is often based on algorithms that require establishing correspondences between endoscopic images. However, reference annotations frequently required to train or validate a method are extremely difficult to obtain because they are typically made by a medical expert with very limited resources, and publicly available data sets are still far too small to capture the wide range of anatomical/scene variance. Crowdsourcing is a new trend that is based on outsourcing cognitive tasks to many anonymous untrained individuals from an online community.

Pose-independent surface matching for intra-operative soft-tissue marker-less registration.

One of the main challenges in computer-assisted soft tissue surgery is the registration of multi-modal patient-specific data for enhancing the surgeon's navigation capabilities by observing beyond exposed tissue surfaces. A new approach to marker-less guidance involves capturing the intra-operative patient anatomy with a range image device and doing a shape-based registration. However, as the target organ is only partially visible, typically does not provide salient features and underlies severe non-rigid deformations, surface matching in this context is extremely challenging.

Malabsorption as a Therapeutic Approach in Bariatric Surgery.

Background: The increasing prevalence of obese patients will lead to a more frequent use of bariatric procedures in the future. Compared to conservative medical therapy, bariatric procedures achieve greater weight loss and superior control of comorbidities, resulting in improved overall mortality.

Methods: A search for current literature regarding mechanisms, indications, and outcomes of bariatric surgery was performed.

Context-aware Augmented Reality in laparoscopic surgery.

Augmented Reality is a promising paradigm for intraoperative assistance. Yet, apart from technical issues, a major obstacle to its clinical application is the man-machine interaction. Visualization of unnecessary, obsolete or redundant information may cause confusion and distraction, reducing usefulness and acceptance of the assistance system.