Localization for capsule endoscopy at UWB frequencies using an experimental multilayer phantom

[EN] Localization inside the human body using ultrawideband (UWB) wireless technology is gaining importance in several medical applications such as capsule endoscopy. Performance analysis of RF based localization techniques are mainly conducted through simulations using numerical human models or through experimental measurements using homogeneous phantoms. One of the most common implemented RF localization approaches uses the received signal strength (RSS). However, to the best of our knowledge, no experimental measurements employing multilayer phantoms are currently available in literature. This paper investigates the performance of RSS-based technique for two-dimensional (2D) localization by employing a two-layer experimental phantom-based setup. Preliminary results on the estimation of the in-body antenna coordinates show that RSS-based method can achieve a location accuracy on average of 0.5-1 cm within a certain range of distances between in-body and on-body antenna.This work was supported by the European Union’s H2020:MSCA:ITN program for the ”Wireless In-body Environment Communication- WiBEC” project under the grant agreement no. 675353. This work was also funded by the Programa de Ayudas de Investigación y Desarrollo (PAID-01-16) from Universitat Politècnica de València and by the Ministerio de Economía y Competitividad, Spain (TEC2014-60258-C2-1-R), by the European FEDER funds.Barbi, M.; Pérez Simbor, S.; García Pardo, C.; Andreu Estellés, C.; Cardona Marcet, N. (2018). Localization for capsule endoscopy at UWB frequencies using an experimental multilayer phantom. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/WCNCW.2018.8369015

Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

Objective: Surgical data science is evolving into a research field that aims to observe everything occurring within and around the treatment process to provide situation-aware data-driven assistance. In the context of endoscopic video analysis, the accurate classification of organs in the field of view of the camera proffers a technical challenge. Herein, we propose a new approach to anatomical structure classification and image tagging that features an intrinsic measure of confidence to estimate its own performance with high reliability and which can be applied to both RGB and multispectral imaging (MI) data. Methods: Organ recognition is performed using a superpixel classification strategy based on textural and reflectance information. Classification confidence is estimated by analyzing the dispersion of class probabilities. Assessment of the proposed technology is performed through a comprehensive in vivo study with seven pigs. Results: When applied to image tagging, mean accuracy in our experiments increased from 65% (RGB) and 80% (MI) to 90% (RGB) and 96% (MI) with the confidence measure. Conclusion: Results showed that the confidence measure had a significant influence on the classification accuracy, and MI data are better suited for anatomical structure labeling than RGB data. Significance: This work significantly enhances the state of art in automatic labeling of endoscopic videos by introducing the use of the confidence metric, and by being the first study to use MI data for in vivo laparoscopic tissue classification. The data of our experiments will be released as the first in vivo MI dataset upon publication of this paper.Comment: 7 pages, 6 images, 2 table

Ontology creation for wireless capsule endoscopy videos

In this paper we study multimedia ontology for Wireless Capsule Endoscopy (WCE) videos by enhancing its existing data structure. The ‘wireless capsule’ is a tiny disposable video camera that transmits 2 ~ 3 frames per second for a period of 8 ~ 11 hours. There are open problems in WCE, such as bleeding detection, as it is hard to identify accurately, using low-level features, i.e., color values. In addition, the physicians have to examine the videos continuously for two hours or more, which becomes restrictive. There have been research attempts to reduce this review time. However, they suffer from low accuracy and sensitivity, and do not process WCE videos with an efficient information data structure. To address this problem, we propose a new data structure named ‘multimedia ontology for WCE videos’ formed by combining medical and multimedia domain knowledge. Ontology represents a structure to describe the concepts and relationships in a specific domain with relevant data and its terminology. We define two types of ontology, i.e., generic and specific ontology. Generic ontology represents the broad concepts in WCE videos, such as medical terms, anatomic information, video format, etc., while specific ontology is a data-driven one including color, location, and region of images. The process of creating multimedia ontology consists of three steps: (1)collection of raw data from WCE videos, such as video data format, feature values, meta-data information and anomalies, (2) classification of the raw data into concepts including generic and specific ontology, and (3) identification of relationship between two concepts such as ‘Is-A’, ‘Part-Of’, and ‘Has-A’. This WCE Ontology structure can be used to better address the open problems by providing 'relevant area focus' from the formed structure and can also be extended to other problems like detection of lesions and polyps

UWB RSS-based Localization for Capsule Endoscopy using a Multilayer Phantom and In Vivo Measurements

[EN] In recent years, the localization for capsule endoscopy applications using ultrawideband (UWB) technology has become an attractive field of investigation due to its potential benefits for patients. The literature concerning performance analysis of radio frequency-based localization techniques for in-body applications at UWB frequencies is very limited. Available studies mainly rely on finite-difference time-domain simulations, using digital human models and on experimental measurements by means of homogeneous phantoms. Nevertheless, no realistic analysis based on multilayer phantom measurements or through in vivo experiment has been reported yet. This paper investigates the performance of the received signal strength-based approach for 2-D and 3-D localizations in the UWB frequency band. For 2-D localization, experimental laboratory measurements using a two-layer phantom-based setup have been conducted. For 3-D localization, data from a recently conducted in vivo experiment have been used. Localization accuracy using path loss models, under ideal and non-ideal channel estimation assumptions, is compared. Results show that, under nonideal channel assumption, the relative localization error slightly increases for the 2-D case but not for the in vivo 3-D case. Impact of receivers selection on the localization accuracy has also been investigated for both 2-D and 3-D cases.This work was supported in part by the European Union's H2020 through the MSCA: ITN Program "Wireless in-Body Environment Communication-WiBEC" under Grant 675353, in part by the Programa de Ayudas de Investigacion y Desarrollo, Universitat Politecnica de Valencia under Grant PAID-01-16, and in part by the Ministerio de Economia y Competitividad, Spain, through the European FEDER Funds under Grant TEC2014-60258-C2-1-R.Barbi, M.; Garcia-Pardo, C.; Nevárez, A.; Pons Beltrán, V.; Cardona Marcet, N. (2019). UWB RSS-based Localization for Capsule Endoscopy using a Multilayer Phantom and In Vivo Measurements. IEEE Transactions on Antennas and Propagation. 67(8):5035-5043. https://doi.org/10.1109/TAP.2019.2916629S5035504367

Semi-automated parallel programming in heterogeneous intelligent reconfigurable environments (SAPPHIRE)

In recent years, as we come closer to approaching physical limits in making smaller (and faster) computer processors, focus has instead been turned toward including multiple processor cores in each device. While this technically allows for more computational power as compared with only one traditional processor core, conventional software can typically only make use of a single processor. Furthermore, we see an increasing number of stream programs that process streams of data such as a stream of images or audio. For stream programs to effectively utilize multi-core processors, multithreading is the key, but it may be difficult to implement in practice depending on the complexity of the programs. We present SAPPHIRE: Semi-Automated Parallel Programming in Heterogeneous Intelligent Reconfigurable Environment, a middleware and SDK for developing multithreaded stream programs. In this middleware, we implement our semi-automated program construction technique which is designed to aid in writing multithreaded software by reducing needed complexity and lines of code written by software developers. We also present a novel static task-scheduling algorithm for stream programs with heterogeneous implementation choices. Our algorithm is capable of scheduling stream programs with provably near-optimal results given a specific set of assumptions, without requiring the unrolling of the task graph. Unrolling the task graph greatly increases the size of the input to the NP-Complete part of the task-scheduling problem as in related work. Finally, we present two case study programs implemented using SAPPHIRE. One case study, EM-Capture, has analyzed over 50 billion frames of endoscopy video in real-time in a real hospital, discerning over 71,000 unique endoscopy procedures. The other case study, EM-Feedback-RT, is a collaborative extension to EM-Capture, and is an attempt to provide real-time quality analysis feedback to physicians during a colonoscopy exam

New Techniques in Gastrointestinal Endoscopy

As result of progress, endoscopy has became more complex, using more sophisticated devices and has claimed a special form. In this moment, the gastroenterologist performing endoscopy has to be an expert in macroscopic view of the lesions in the gut, with good skills for using standard endoscopes, with good experience in ultrasound (for performing endoscopic ultrasound), with pathology experience for confocal examination. It is compulsory to get experience and to have patience and attention for the follow-up of thousands of images transmitted during capsule endoscopy or to have knowledge in physics necessary for autofluorescence imaging endoscopy. Therefore, the idea of an endoscopist has changed. Examinations mentioned need a special formation, a superior level of instruction, accessible to those who have already gained enough experience in basic diagnostic endoscopy. This is the reason for what these new issues of endoscopy are presented in this book of New techniques in Gastrointestinal Endoscopy