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Search results for: SURGICAL INSTRUMENT TRACKING
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Surgical tool tracking by on-line selection of structural correlation filters
PublicationIn visual tracking of surgical instruments, correlation filtering finds the best candidate with maximal correlation peak. However, most trackers only consider capturing target appearance but not target structure. In this paper we propose surgical instrument tracking approach that integrates prior knowledge related to rotation of both shaft and tool tips. To this end, we employ rigid parts mixtures model of an instrument. The rigidly...
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Instrument detection and pose estimation with rigid part mixtures model in video-assisted surgeries
PublicationLocalizing instrument parts in video-assisted surgeries is an attractive and open computer vision problem. A working algorithm would immediately find applications in computer-aided interventions in the operating theater. Knowing the location of tool parts could help virtually augment visual faculty of surgeons, assess skills of novice surgeons, and increase autonomy of surgical robots. A surgical tool varies in appearance due to...
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Pose-Configurable Generic Tracking of Elongated Objects
PublicationElongated objects have various shapes and can shift, rotate, change scale, and be rigid or deform by flexing, articulating, and vibrating, with examples as varied as a glass bottle, a robotic arm, a surgical suture, a finger pair, a tram, and a guitar string. This generally makes tracking of poses of elongated objects very challenging. We describe a unified, configurable framework for tracking the pose of elongated objects, which...
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Nanoparticle Tracking Analysis of Urinary Extracellular Vesicle Proteins as a New Challenge in Laboratory Medicine
PublicationUrinary extracellular vesicle (uEV) proteins may be used as specific markers of kidney damage in various pathophysiological conditions. The nanoparticle-tracking analysis (NTA) appears to be the most useful method for the analysis of uEVs due to its ability to analyze particles below 300 nm. The NTA method has been used to measure the size and concentration of uEVs and also allows for a deeper analysis of uEVs based on their protein...
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A new diagnostic IR-thermal imaging method for evaluation of cardiosurgery procedures
PublicationTwo methods for monitoring the state of the myocardium during cardiosurgical interventions based on thermal IR imaging are presented below. These methods, called static thermography and active dynamic thermography (ADT), use information about the distribution of temperature on the surface, and an external excitation source to induce thermal transient processes in a tested object. Recording the time series of thermograms allows...
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The role of rewards and demands in burnout among surgical nurses
PublicationObjective: Job rewards have both, an intrinsic and an extrinsic motivational potential, and lead to employees’ development as well as help them to achieve work goals. Rewards can balance job demands and protect from burnout. Due to changes on the labour market, new studies are needed. The aim of our study was to examine the role of demands and individual rewards (and their absence) in burnout among surgical nurses. Materials and...
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Shape-Based Pose Estimation of Robotic Surgical Instruments
PublicationWe describe a detector of robotic instrument parts in image-guided surgery. The detector consists of a huge ensemble of scale-variant and pose-dedicated, rigid appearance templates. The templates, which are equipped with pose-related keypoints and segmentation masks, allow for explicit pose estimation and segmentation of multiple end-effectors as well as fine-grained non-maximum suppression. We train the templates by grouping examples...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublicationThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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Musical Instrument Identification Using Deep Learning Approach
PublicationThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Mariusz Kaczmarek dr hab. inż.
PeopleReceived M.Sc., Eng. in Electronics in 1995 from Gdansk University of Technology, Ph.D. in Medical Electronics in 2003 and habilitation in Biocybernetics and Biomedical Engineering in 2017. He was an investigator in about 13 projects receiving a number of awards, including four best papers, practical innovations (7 medals and awards) and also the Andronicos G. Kantsios Award and Siemens Award. Main research activities: the issues...