Fouille de séquences d'images médicales. Application en chirurgie mini-invasive augmentée

In this thesis, we are interested in computer-aided ophthalmic surgery. In this goal, we propose to use surgery videos already stored in database and associated with contextual information (data patients, diagnostics ... etc). During the surgery, the surgeon is focused on his task. We try to improve the surgical procedures by proposing a system able, at any time, to guide the surgery steps by generating surgical warnings or recommendations if the current surgery shares signs of complications with already stored videos. Our goal is to develop methods and a system to select in the databases videos similar to a video stream captured by a digital camera monitoring the surgery (query). Our work will therefore implement methods related to Content Based Video Retrieval (CBVR) and Case-Based Reasoning (CBR). The methods are evaluated on three databases. The first two databases are collected at Brest University Hospital (France): the epiretinal membrane surgery dataset and the cataract surgery dataset. Third, in order to assess its generality, the system is applied to a large dataset of movie clips (Holywood) with classified human actions. To caracterize our videos, we proposed three original indexing methods derived from the compressed ``MPEG-4 AVC/H.264'' video stream. 1) A global method is based on motion histogram created for every frame of a compressed video sequence to extract motion direction and intensity statistics. 2) A local method combine segmentation and tracking to extract region displacements between consecutive I-frames and therefore characterize region trajectories. 3) To reduce the loss of information caused by using only the I-frames, we constructed a summary of each video based on a selection of the Group Of Pictures (GOP defined in the standard of compression). An originality of these methods comes from the use of the compressed domain, they not rely on standard methods, such as the optical flow, to characterize motion in videos. Instead, motion is directly extracted from the compressed MPEG stream. The goal is to provide a fast video characterization. Once videos are characterized, search is made by computing, within the meaning of a given metric, the distance between the signature of the query video and the signature of videos in the database. This computing can select videos as answer to the query without any semantic meaning. For this we use three methods. DTW (Dynamic Time Warping) provides an effective distance between two sequences of images. This algorithm is at the origin of the fast algorithm (FDTW) that we use to compare signatures in the first method. To compare signatures resulting from approach based on region motion trajectories, we propose to use a combination of FDTW and EMD (Earth Mover's Distance). The proposed extension of FDTW is referred to as EFDTW. To improve the retrieval result, we introduce an optimization process for computing distances between signature, by using genetic algorithms. The results obtained on the two medical databases are satisfactory. Thus, the mean precision at five reaches 79% (4 videos similar to the query video) on the epiretinal membrane surgery dataset and 72,69% (3 to 4 videos similar to the query video) on the cataract surgery dataset.Dans cette thèse, nous nous intéressons à l'aide à la décision lors d'interventions chirurgicales. Dans ce but, nous proposons d'utiliser des enregistrements vidéos acquis lors d'interventions chirurgicales antérieures, vidéos numérisées et archivées dans des dossiers d'intervention, contenant toutes les informations relatives à leur déroulement. Au cours de l'opération, le chirurgien ne peut pas consulter lui même des dossiers et vidéos déjà archivées car il est totalement concentré sur l'acte; par contre des outils d'analyse automatique en temps réel des images acquises en cours d'opération pourraient permettre cette utilisation de séquences déjà archivées, avec comme applications directes : des alertes en cas de problème, des informations sur les suites de tel ou tel geste dans des situations opératoires voisines (opération, caractéristiques patient, etc ...), des conseils sur les décisions. Notre objectif est donc de développer des méthodes permettant de sélectionner dans des archives des vidéos similaires à la vidéo proposée en requête. Nous nous appuyons pour cela sur la recherche de vidéos par le contenu (CBVR : Content Based Video Retrieval) et le raisonnement à base de cas (CBR : Case Based Reasoning). Les méthodes sont évaluées sur trois bases de données. Les deux premières bases de données étudiées sont des bases réalisées en chirurgie ophtalmologique, en collaboration avec le service d'ophtalmologie du CHRU de Brest : une base de chirurgie de pelage de membrane de la rétine et une base de chirurgie de la cataracte. La troisième base est la base de clips vidéo Hollywood, utilisée pour montrer la généricité des méthodes proposées. Pour caractériser les vidéos, nous proposons trois méthodes originales d'indexation à partir du domaine compressé : 1) une première méthode consiste à caractériser globalement la vidéo en utilisant des histogrammes de directions de mouvement, 2) une deuxième méthode est basée sur une segmentation spatio-temporelle et sur le suivi des régions entre deux images I, pour construire une signature décrivant la trajectoire des régions identifiées comme les plus importantes visuellement, 3) la troisième méthode est une variante de la deuxième méthode : afin de réduire la perte d'information engendrée en utilisant uniquement les images I, nous avons construit un résumé de la vidéo basé sur une sélection des Group Of Pictures (groupes d'images définis dans la norme de compression). Une des originalités de ces trois méthodes est d'utiliser les données vidéos dans le domaine compressé. Ce choix nous permet d'accéder à des éléments caractérisant les vidéos d'une manière rapide et efficace, sans devoir passer par la reconstruction totale du flux vidéo à partir du flux compressé

Fractional Reverse Coposn's Inequalities via Conformable Calculus on Time Scales

This paper provides novel generalizations by considering the generalized conformable fractional integrals for reverse Copson's type inequalities on time scales. The main results will be proved using a general algebraic inequality, chain rule, Hölder's inequality, and integration by parts on fractional time scales. Our investigations unify and extend some continuous inequalities and their corresponding discrete analogues. In addition, when α = 1, we obtain some well-known time scale inequalities due to Hardy, Copson, Bennett, and Leindler inequalities

Efficient approximate analytical technique to solve nonlinear coupled Jaulent–Miodek system within a time-fractional order

In this article, we considered the nonlinear time-fractional Jaulent–Miodek model (FJMM), which is applied to modeling many applications in basic sciences and engineering, especially physical phenomena such as plasma physics, fluid dynamics, electromagnetic waves in nonlinear media, and many other applications. The Caputo fractional derivative (CFD) was applied to express the fractional operator in the mathematical formalism of the FJMM. We implemented the modified generalized Mittag-Leffler method (MGMLFM) to show the analytical approximate solution of FJMM, which is represented by a set of coupled nonlinear fractional partial differential equations (FPDEs) with suitable initial conditions. The suggested method produced convergent series solutions with easily computable components. To demonstrate the accuracy and efficiency of the MGMLFM, a comparison was made between the solutions obtained by MGMLFM and the known exact solutions in some tables. Also, the absolute error was compared with the absolute error provided by some of the other famous methods found in the literature. Our findings confirmed that the presented method is easy, simple, reliable, competitive, and did not require complex calculations. Thus, it can be extensively applied to solve more linear and nonlinear FPDEs that have applications in various areas such as mathematics, engineering, and physics

O poema//processo de Wlademir Dias-Pino: entre escritura e visualidade

O presente artigo apresenta o movimento do poema//processo, criado pelo poeta mato-grossense Wlademir Dias-Pino em 1967, que envolveu uma série de poetas e artistas e marcou uma passagem importante na história das vanguardas da literatura e da arte brasileiras. A partir dos principais conceitos do movimento, trataremos das imbricações entre poesia e artes visuais utilizando três abordagens inter-relacionadas na poesia de Dias-Pino: a separação entre as ideias de estrutura e de processo; a separação entre as ideias de língua e de linguagem; e a recusa radical à escrita alfabética. Também serão marcados os aspectos que aproximam e que separam o poema//processo da chamada poesia visual e da Poesia Concreta de Haroldo e Augusto de Campos e de Décio Pignatari

Efficacy and safety of cardioprotective drugs in chemotherapy-induced cardiotoxicity: an updated systematic review & network meta-analysis

BACKGROUND: Cancer patients receiving chemotherapy have an increased risk of cardiovascular complications. This limits the widespread use of lifesaving therapies, often necessitating alternate lower efficacy regimens, or precluding chemotherapy entirely. Prior studies have suggested that using common cardioprotective agents may attenuate chemotherapy-induced cardiotoxicity. However, small sample sizes and conflicting outcomes have limited the clinical significance of these results. HYPOTHESIS: A comprehensive network meta-analysis using updated and high-quality data can provide more conclusive information to assess which drug or drug class has the most significant effect in the management of chemotherapy-induced cardiotoxicity. METHODS: We performed a literature search for randomized controlled trials (RCTs) investigating the effects of cardioprotective agents in patients with chemotherapy-induced cardiotoxicity. We used established analytical tools (netmeta package in RStudio) and data extraction formats to analyze the outcome data. To obviate systematic bias in the selection and interpretation of RCTs, we employed the validated Cochrane risk-of-bias tools. Agents included were statins, aldosterone receptor antagonists (MRAs), ACEIs, ARBs, and beta-blockers. Outcomes examined were improvement in clinical and laboratory parameters of cardiac function including a decreased reduction in left ventricular ejection fraction (LVEF), clinical HF, troponin-I, and B-natriuretic peptide levels. RESULTS: Our study included 33 RCTs including a total of 3,285 patients. Compared to control groups, spironolactone therapy was associated with the greatest LVEF improvement (Mean difference (MD) = 12.80, [7.90; 17.70]), followed by enalapril (MD = 7.62, [5.31; 9.94]), nebivolol (MD = 7.30, [2.39; 12.21]), and statins (MD = 6.72, [3.58; 9.85]). Spironolactone was also associated with a significant reduction in troponin elevation (MD =  - 0.01, [- 0.02; - 0.01]). Enalapril demonstrated the greatest BNP reduction (MD =  - 49.00, [- 68.89; - 29.11]), which was followed by spironolactone (MD =  - 16.00, [- 23.9; - 8.10]). Additionally, patients on enalapril had the lowest risk of developing clinical HF compared to the control population (RR = 0.05, [0.00; 0.75]). CONCLUSION: Our analysis reaffirmed that statins, MRAs, ACEIs, and beta-blockers can significantly attenuate chemotherapy-induced cardiotoxicity, while ARBs showed no significant effects. Spironolactone showed the most robust improvement of LVEF, which best supports its use among this population. Our analysis warrants future clinical studies examining the cardioprotective effects of cardiac remodeling therapy in cancer patients treated with chemotherapeutic agents

An industrial IoT-based blockchain-enabled secure searchable encryption approach for healthcare systems using neural network

The IoT refers to the interconnection of things to the physical network that is embedded with software, sensors, and other devices to exchange information from one device to the other. The interconnection of devices means there is the possibility of challenges such as security, trustworthiness, reliability, confidentiality, and so on. To address these issues, we have proposed a novel group theory (GT)-based binary spring search (BSS) algorithm which consists of a hybrid deep neural network approach. The proposed approach effectively detects the intrusion within the IoT network. Initially, the privacy-preserving technology was implemented using a blockchain-based methodology. Security of patient health records (PHR) is the most critical aspect of cryptography over the Internet due to its value and importance, preferably in the Internet of Medical Things (IoMT). Search keywords access mechanism is one of the typical approaches used to access PHR from a database, but it is susceptible to various security vulnerabilities. Although blockchain-enabled healthcare systems provide security, it may lead to some loopholes in the existing state of the art. In literature, blockchainenabled frameworks have been presented to resolve those issues. However, these methods have primarily focused on data storage and blockchain is used as a database. In this paper, blockchain as a distributed database is proposed with a homomorphic encryption technique to ensure a secure search and keywords-based access to the database. Additionally, the proposed approach provides a secure key revocation mechanism and updates various policies accordingly. As a result, a secure patient healthcare data access scheme is devised, which integrates blockchain and trust chain to fulfill the efficiency and security issues in the current schemes for sharing both types of digital healthcare data. Hence, our proposed approach provides more security, efficiency, and transparency with cost-effectiveness. We performed our simulations based on the blockchain-based tool Hyperledger Fabric and OrigionLab for analysis and evaluation. We compared our proposed results with the benchmark models, respectively. Our comparative analysis justifies that our proposed framework provides better security and searchable mechanism for the healthcare system

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Study and evaluation of electronic transport property for an InAlN based on Monte Carlo

The emergence of the semiconductors III-N with heterojunction structures has made it possible to study a wide range of two-dimensional phenomena. This paper devotes to simulate the characteristics of the InAlN material, taking into ac-count temperature and doping as dependencies of conduction properties and performance using MOCASIM of the Tcad-Silvaco software. For the electronic transport model analyzing, we adopted most of the predominant mechanisms using various scattering effects including: optical phonon scattering, acoustic phonon scattering through deformation potential and piezoelectric potential, ionized impurity scattering, and grain boundary scattering. As expected, the carrier transports in the GaN layer are affected by the spontaneous polarization of the InAlN layer. To interact that, the diffusion of grain boundaries has been switched from the diffusion of ionized impurities by the deposition of InAlN. In order to achieve the most improvement possible for the electron transferring in terms of thickness and alloy composition related to the improvement of super-deposited layers. The confinement of sub-bands in channel quantum well is also taken into account in the computation of electron mobility. In the end, the adopted electron model is improved by including the effects of deep electron traps