Publications by authors named "N P Sgouros"
Background: Various techniques have been proposed in the literature for phase and tool recognition from laparoscopic videos. In comparison, research in multilabel annotation of still frames is limited.
Methods: We describe a framework for multilabel annotation of images extracted from laparoscopic cholecystectomy (LC) videos based on multi-instance multiple-label learning.
Background: Various sensors and methods are used for evaluating trainees' skills in laparoscopic procedures. These methods are usually task-specific and involve high costs or advanced setups.
Methods: In this paper, we propose a novel manoeuver representation feature space (MRFS) constructed by tracking the vanishing points of the edges of the graspers on the video sequence frames, acquired by the standard box trainer camera.
Accumulating data have shown that elimination of atrial fibrillation (AF) sources should be the goal in persistent AF ablation. Pulmonary vein isolation, linear lesions and complex fractionated atrial electrograms (CFAEs) ablation have shown limited efficacy in patients with persistent AF. A combined approach using voltage, CFAEs and dominant frequency (DF) mapping may be helpful for the identification of AF sources and subsequent focal substrate modification.
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- There are various 3D techniques for capturing and presenting autostereoscopic content, with integral imaging (InI) standing out for its ability to create high-quality full-color 3D visuals and two-dimensional parallax.
- Misalignments between lens arrays and camera sensors can lead to geometric distortions that negatively affect the 3D viewing experience as the image passes through processing stages.
- The proposed method addresses these distortions by using an edge-linking technique to identify and rectify the perspective issues in integral images, employing triangulation and statistical methods to improve the accuracy of the lens array's grid structure, backed by comprehensive experimental results.
In most integral image analysis and processing tasks, accurate knowledge of the internal image structure is required. In this paper we present a robust framework for the accurate rectification of perspectively distorted integral images based on multiple line segment detection. The use of multiple line segments increases the overall fault tolerance of our framework providing strong statistical support for the rectification process.
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