Situation Interpretation for Knowledge- and Model Based Laparoscopic Surgery

To manage the influx of information into surgical practice, new man-machine interaction methods are necessary to prevent information overflow. This work presents an approach to automatically segment surgeries into phases and select the most appropriate pieces of information for the current situation. This way, assistance systems can adopt themselves to the needs of the surgeon and not the other way around

Toward a Knowledge-Driven Context-Aware System for Surgical Assistance

Complex surgeries complications are increasing, thus making an efficient surgical assistance is a real need. In this work, an ontology-based context-aware system was developed for surgical training/assistance during Thoracentesis by using image processing and semantic technologies. We evaluated the Thoracentesis ontology and implemented a paradigmatic test scenario to check the efficacy of the system by recognizing contextual information, e.g. the presence of surgical instruments on the table. The framework was able to retrieve contextual information about current surgical activity along with information on the need or presence of a surgical instrument

CholecTrack20: A Dataset for Multi-Class Multiple Tool Tracking in Laparoscopic Surgery

Tool tracking in surgical videos is vital in computer-assisted intervention for tasks like surgeon skill assessment, safety zone estimation, and human-machine collaboration during minimally invasive procedures. The lack of large-scale datasets hampers Artificial Intelligence implementation in this domain. Current datasets exhibit overly generic tracking formalization, often lacking surgical context: a deficiency that becomes evident when tools move out of the camera's scope, resulting in rigid trajectories that hinder realistic surgical representation. This paper addresses the need for a more precise and adaptable tracking formalization tailored to the intricacies of endoscopic procedures by introducing CholecTrack20, an extensive dataset meticulously annotated for multi-class multi-tool tracking across three perspectives representing the various ways of considering the temporal duration of a tool trajectory: (1) intraoperative, (2) intracorporeal, and (3) visibility within the camera's scope. The dataset comprises 20 laparoscopic videos with over 35,000 frames and 65,000 annotated tool instances with details on spatial location, category, identity, operator, phase, and surgical visual conditions. This detailed dataset caters to the evolving assistive requirements within a procedure.Comment: Surgical tool tracking dataset paper, 15 pages, 9 figures, 4 table

Workflow-based Context-aware Control of Surgical Robots

Surgical assistance system such as medical robots enhanced the capabilities of medical procedures in the last decades. This work presents a new perspective on the use of workflows with surgical robots in order to improve the technical capabilities and the ease of use of such systems. This is accomplished by a 3D perception system for the supervision of the surgical operating room and a workflow-based controller, that allows to monitor the surgical process using workflow-tracking techniques

Surgical Smoke Evacuation Guidelines: Compliance Among Perioperative Nurses

Smoke (plume) is produced when tissue is cut or coagulated with lasers or electrosurgery devices during surgery. Research has documented that surgical smoke creates a serious workplace hazard for over 500,000 healthcare workers. Toxic gases create an offensive odor, small particulate matter causes respiratory complications, and pathogens may be transmitted within the surgical smoke to the surgical team. Previous research notes that smoke evacuation recommendations are not being consistently followed by perioperative nurses. The purpose of this study is to determine key indicators that are associated with compliance with smoke evacuation recommendations by perioperative nurses. The Diffusion of Innovation theory by Rogers serves as the model since it describes key indicators for the adoption of an innovation, including individual innovativeness, perceptions of the innovation attributes, and organizational innovativeness. A descriptive explanatory/exploratory study was conducted using a validated and piloted survey that consisted of both expert-generated questions and adaptations of previously proven measures. A population of AORN (Association of periOperative Registered Nurses) staff nurse members who have e-mail addresses (N=20,272) was targeted as the universe. A random sampling consisting of 4000 nurses were invited to respond to a web-based survey during a two-month period. There were 777 completed responses representing a 19.4 percent response rate. The SPSS statistical computer package was employed to analyze the data using frequency/descriptive statistical techniques and bivariate analyses to examine the relationship between the key indicators and compliance with smoke evacuation recommendations. Major findings reveal that specific key indicators influencing compliance include increased knowledge and training, positive perceptions about the complexity of the recommendations, and larger facilities with increased specialization, interconnectedness, and leadership support. The study outcomes are planned to be disseminated via lectures and articles. Promoting a safe surgical environment is a top priority for perioperative nurses. By identifying key predictors that influence compliance with smoke evacuation practices, a better understanding of the many factors that influence perioperative nurse practices is fostered. Nurse training programs can be developed that directly target and address these key predictors so that a safe and healthy surgical environment free from surgical smoke can be promoted

Kontextsensitivität für den Operationssaal der Zukunft

The operating room of the future is a topic of high interest. In this thesis, which is among the first in the recently defined field of Surgical Data Science, three major topics for automated context awareness in the OR of the future will be examined: improved surgical workflow analysis, the newly developed event impact factors, and as application combining these and other concepts the unified surgical display.Der Operationssaal der Zukunft ist ein Forschungsfeld von großer Bedeutung. In dieser Dissertation, die eine der ersten im kürzlich definierten Bereich „Surgical Data Science“ ist, werden drei Themen für die automatisierte Kontextsensitivität im OP der Zukunft untersucht: verbesserte chirurgische Worflowanalyse, die neuentwickelten „Event Impact Factors“ und als Anwendungsfall, der diese Konzepte mit anderen kombiniert, das vereinheitlichte chirurgische Display