Computer-Aided Surgical Quality Assessment in Medical Endoscopy (CASQADE) 1
Laparoscopy requires specific psychomotor skills, which are difficult to learn and result in prolonged learning curves. These psychomotor skills have direct impact on the operative performance. In order to assess surgical quality, medical experts inspect and analyze unedited video footage for the occurrence of technical errors using validated rating schemes. This process is currently done manually, which is time-consuming and error-prone. In this project, we aim to improve surgical quality assessment (SQA) through software support.
We want to investigate fundamental aspects of computer-aided SQA, and reach the following goals: (1) accelerate the process of SQA and thereby make it more feasible, (2) perform semi-automatic SQA, with automatic suggestions of video segments to inspect by a human expert, and (3) improve the quality of SQA itself (e.g., through automatic detection of subtle technical errors that may be missed by a human assessor). We want to achieve this by applying the following three fundamental technical methods: (I) semantics/knowledge modeling, (II) automatic video content analysis, and (III) appropriate video interaction features. More specifically, we want to learn and model the major procedural steps of SQA in laparoscopy, and use this semantic knowledge both for supporting semi-automatic content detection and for creating interactive tools.
Klaus Schoeffmanna, Heinrich Hussleinb, Laszlo B ̈osz ̈ormenyia
a Alpen-Adria-Universität Klagenfurt Institut für Informationstechnologie Universitä̈tsstraße 65-67
A-9020 Klagenfurt, Austria
b Medizinische Universität Wien / AKH Wien Universitätsklinik für Frauenheilkunde Wä̈hringer Gürtel 18-20
A-1090 Wien, Austria
1 This is a revision of the rejected FWF application P 29041-B31 (Surgical Quality Assessment in Gynecologic Laparoscopy – SQUASH), according to the helpful and encouraging reviews.
Bildnachweis Grafik: Endometriosezentrum der Medizinischen Universität Wien