Vessel recognition in ultrasound images using machine learning techniques

Purpose: Ultrasound is an imaging modality that is commonly used during cardiovascular surgeries globally. The purpose of this thesis is to investigate how machine learning techniques can be used to identify vessel properties and probe orientation in cardiac ultrasound images. The ultimate goal is developing a machine learning algorithm that can automatically recognize vessels in the region of interest with high mean average precision, identify vessel orientation, and run in near real-time. Method: This thesis present a thoroughly data exploration of ultrasound images acquired from a multicenter study. A pilot study of three different object detection models; Yolo, RetinaNet and EfficientDet, was done to find the best model fit for the dataset in the thesis. The three object detection models were trained, tuned and evaluated on the ultrasound data. The object detection model that performed the best after the pilot study was explored further. Yolo outperformed the other models and was therefore chosen as the object detection model for the final study. To overcome the dataset's class imbalance and size problem, data augmentation, resizing and upscaling of the ultrasound images were employed. The resulting data was used to train multiple yolo models with varying hyperparameter tunings. Model selection was then performed on these trained models, and the final model was evaluated on test data. Results: The final model achieved an overall mean average precision at 50\% at 71.77\%. The vessel orientation achieved a mean average precision at 64.6\% for the longitudinal orientation and 75.8\% for the transversal orientation. The model found it easier to locate the aorta compared to the anastomosis, which proved to be more challenging. The speed of the inference of all of these task was 5.6 milliseconds. Although the overall mean average precision was lower than the objective in this thesis, the model excelled in terms of speed. Conclusion: In conclusion, this thesis explored the application of machine learning techniques on ultrasound data for vessel recognition and orientation. Although the final model did not improve the state of the art, the research from this master thesis can serve as a starting point for future reasearch in the field. It represents pioneering work in utilizing a multicenter dataset for machine learning on ultrasound images, providing valuable groundwork and shedding light on the feasibility and potential of machine learning in intraoperative ultrasound.Masteroppgave i medisinsk teknologiMTEK39

Adipocytes, aldosterone and obesity-related hypertension

Understanding the mechanisms linking obesity with hypertension is important in the current obesity epidemic as it may improve therapeutic interventions. Plasma aldosterone levels are positively correlated with body mass index and weight loss in obese patients is reported to be accompanied by decreased aldosterone levels. This suggests a relationship between adipose tissue and the production/secretion of aldosterone. Aldosterone is synthesized principally by the adrenal glands, but its production may be regulated by many factors, including factors secreted by adipocytes. In addition, studies have reported local synthesis of aldosterone in extra-adrenal tissues, including adipose tissue. Experimental studies have highlighted a role for adipocyte-secreted aldosterone in the pathogenesis of obesity-related cardiovascular complications via the mineralocorticoid receptor. This review focuses on how aldosterone secretion may be influenced by adipose tissue and the importance of these mechanisms in the context of obesity-related hypertension

Tate Cohomology of Finite Dimensional Hopf Algebras

Let A be a finite dimensional Hopf algebra over a field k. In this dissertation, we study the Tate cohomology Ĥ* (A, k) and Tate-Hochschild cohomology (HH) ̂* (A, A) of A, and their properties. We introduce cup products that make them become graded-commutative rings and establish the relationship between these rings. In particular, we show Ĥ* (A, k) is an algebra direct summand of (HH) ̂* (A, A) as a module over Ĥ* (A, k). When A is a finite group algebra RG over a commutative ring R, we show that the Tate-Hochschild cohomology ring (HH) ̂* (RG, RG) of RG is isomorphic to a direct sum of the Tate cohomology rings of the centralizers of conjugacy class representatives of G. Moreover, our main result provides an explicit formula for the cup product in (HH) ̂* (RG, RG) with respect to this decomposition. When A is symmetric, we show that there are finitely generated A-modules whose Tate cohomology is not finitely generated over the Tate cohomology ring Ĥ* (A, k) of A. It turns out that if a module in a connected component of the stable Auslander-Reiten quiver associated to A has finitely generated Tate cohomology, then so does every module in that component

Continuité et discontinuité de la dépression chez les jeunes Canadiens en transition de l'adolescence à l'âge adulte : portrait descriptif et facteurs de risque

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

DYNAMIC LOCATION DETERMINATION THROUGH SHORT RANGE NEIGHBOR DISCOVERY

Techniques are presented herein that support a close-proximity, ultrasound-based discovery and data exchange capability that provides a non-intrusive method for exchanging data (such as, for example, location information) between devices that share the same airspace. Using ultrasonic sound, information may be shared between any device capable of transmitting and/or receiving ultrasonic sound waves and elements of a network or building infrastructure allowing for the exchange of very specific and dynamic location data. One immediate use case for such technology is in the handling of emergency service (e.g., 911) calls where time and accuracy are critical. The presented techniques may find use in any number of other environments or scenarios including, for example, security and safety, an Internet of things (IoT) setting, a retail establishment, capacity planning, contact tracing, etc

Students’ Perceptions on Blended Synchronous Learning in the Postcrisis Era

With the severe impacts of the Covid-19 pandemic, the educational systems have to be reformed and evolved. Blended synchronous learning has become an attractive tendency in education worldwide as the technology has mushroomed recently and attracts a vast number of users and researchers. Therefore, the current study was conducted to investigate students’ overall perceptions of blended synchronous learning as well as its benefits and challenges. 163 participants in the study have experienced ENT courses in a blended synchronous learning environment for 105 hours within 7 weeks. The instrument employed in the quantitative phase was 27 items adapted from studies by Rahman et al. (2015), López-Pérez et al. (2011), and Wu et al. (2010). Additionally, semi-structured interviews were used to have a deeper understanding of the research issues. Results indicate that more than half of participants had good perceptions about the blended synchronous learning environment and perceived various benefits as well as challenges of it. Moreover, these findings are supplemented with illustrative quotes from interview transcripts to compare and contrast with previous findings reported in the literature, and therefore this study contributes to the field by offering the learners\u27 voices

Quality properties Of Vietnamese cocoa liquors

Vietnam (VN) is an emerging country targeting cocoa as a potential industrial domain. It is however still unclear how the quality of VN cocoa liquors can be positioned in the world cocoa supply. Three VN cocoa liquors exhibiting high to intermediate acidity (pH: 4.7 – 5.2) were selected to produce dark chocolate (48.0% sugar, 17.6% cocoa solids, 34.0% cocoa butter and 0.4% lecithin). A comparison study was conducted to investigate the difference between VN and Ghanaian (GH; pH: 5.6) dark chocolates in terms of Casson flow properties (yield stress sCA and viscosity hCA), hardness (F 20°C and F 30°C), water-soluble organic acid content, aroma profile and sensory evaluation. The impact of pre-treatments of cocoa liquor by ball-milling at different fat contents and conching (-C) was also examined

Control of robot-camera system with actuator's dynamics to track moving object

This study presents a solution to the control of robot–camera system with actuator's dynamics to track a moving object where many uncertain parameters exist in the system’s dynamics. After modeling and analyzing the system, this paper suggests a new control method using an on-line learning neural network in closed-loop to control the Pan-Tilt platform that moves the Camera to keep track an unknown moving object. The control structure based on the image feature error determines the necessary rotational velocities on the Pan joint and Tilt joint and computes the voltage controlling the DC motor in joints such that the object image should always be at the center point in the image plane. The global asymptotic stability of the closed-loop is proven by the Lyapunov direct stability theory. Simulation results on Matlab show the system tracking fast and stable

Overview of the VLSP 2022 -- Abmusu Shared Task: A Data Challenge for Vietnamese Abstractive Multi-document Summarization

This paper reports the overview of the VLSP 2022 - Vietnamese abstractive multi-document summarization (Abmusu) shared task for Vietnamese News. This task is hosted at the 9$^{th}$ annual workshop on Vietnamese Language and Speech Processing (VLSP 2022). The goal of Abmusu shared task is to develop summarization systems that could create abstractive summaries automatically for a set of documents on a topic. The model input is multiple news documents on the same topic, and the corresponding output is a related abstractive summary. In the scope of Abmusu shared task, we only focus on Vietnamese news summarization and build a human-annotated dataset of 1,839 documents in 600 clusters, collected from Vietnamese news in 8 categories. Participated models are evaluated and ranked in terms of \texttt{ROUGE2-F1} score, the most typical evaluation metric for document summarization problem.Comment: VLSP 202