POST-IVUS: A perceptual organisation-aware selective transformer framework for intravascular ultrasound segmentation

Intravascular ultrasound (IVUS) is recommended in guiding coronary intervention. The segmentation of coronary lumen and external elastic membrane (EEM) borders in IVUS images is a key step, but the manual process is time-consuming and error-prone, and suffers from inter-observer variability. In this paper, we propose a novel perceptual organisation-aware selective transformer framework that can achieve accurate and robust segmentation of the vessel walls in IVUS images. In this framework, temporal context-based feature encoders extract efficient motion features of vessels. Then, a perceptual organisation-aware selective transformer module is proposed to extract accurate boundary information, supervised by a dedicated boundary loss. The obtained EEM and lumen segmentation results will be fused in a temporal constraining and fusion module, to determine the most likely correct boundaries with robustness to morphology. Our proposed methods are extensively evaluated in non-selected IVUS sequences, including normal, bifurcated, and calcified vessels with shadow artifacts. The results show that the proposed methods outperform the state-of-the-art, with a Jaccard measure of 0.92 for lumen and 0.94 for EEM on the IVUS 2011 open challenge dataset. This work has been integrated into a software QCU-CMS2 to automatically segment IVUS images in a user-friendly environment

Medical image segmentation with limited data

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Simone Balocco[en] Ischemic Heart Disease (IHD) is one of the leading causes of mortality in Spain; early diagnosis is key. Intravenous ultrasound imaging (IVUS) can help identify symptoms of IHD, at the cost of segmenting a large volume of frames by medical professionals. While promising, automated image segmentation using Convolutional Neural Networks (CNN) suffer from sample scarcity: a large amount of parameters is often used, and medical imaging datasets are typically small and costly to acquire and label. In this report we study and compare state of the art methods used to deal with sample scarcity. In particular we introduce data augmentation methodologies, specialized training losses and transfer learning methods, and compare their performance on IVUS segmentation of the media and lumen or the artery. Additionally we introduce a promising paradigm, few-shot segmentation, and provide an initial implementation using PFENet. This implementation can avoid significant overfitting, even when trained with a single example, outperforming traditional CNNs on the same segmentation problem

Modeling and simulation of arterial walls with focus on damage and residual stresses

Die vorliegende Arbeit behandelt die kontinuumsmechanische Modellierung von Arterienwänden. Ein Schwerpunkt liegt in der Konstruktion von anisotropen Schädigungsmodellen zur Beschreibung von Schädigungseffekten in Arterienwänden, wie sie bei therapeutischen Maßnahmen auftreten. Solche Schädigungseffekte gelten als einer der wesentlichen Faktoren für eine erfolgreiche Behandlung von atherosklerotisch degenerierten Arterien mittels Ballonangioplastie. Ein weiterer Schwerpunkt liegt in der Erarbeitung eines numerischen Modells zur Berücksichtigung von Eigenspannungen in Arterienwänden. Eigenspannungen beeinflussen die Spannungsverteilung in Umfangsrichtung derart, dass sie zu einer Verringerung der Spannungsgradienten in der Arterienwand beitragen. Hierauf aufbauend wird ein neuer Ansatz zur Implementierung von Eigenspannungen vorgeschlagen. Alle Modelle werden an experimentelle Daten angepasst und auf die numerische Simulation von patientenspezifischen Arterienwänden angewendet. Die Quasi-Inkompressibilität des Materials wird zum einen durch die Verwendung einer Penalty-Methode und zum anderen über einen Augmented-Lagrange Ansatz erfüllt. Beide Methoden werden hinsichtlich ihres Einflusses auf die Robustheit numerischer Simulationen untersucht.The present work deals with the continuum-mechanical modeling and analysis of arterial walls. One focus is on the construction of anisotropic damage models that are able to reflect damage effects in arterial tissues under therapeutic loading. Damage effects are assumed to be a main contributor to the success of a balloon angioplasty, which is a method of treatment of atherosclerotic arteries. Another main focus is on the elaboration of a numerical model for the incorporation of residual stresses in arterial walls. Residual stresses influence the circumferential stress distribution in such a way that they prevent large stress gradients in the arterial wall. Thus, a novel approach for the implementation of residual stresses is proposed. All models are adjusted to experimental data and applied to numerical simulations of patient-specific arterial walls. The quasi-incompressibility constraint is ensured by using the Penalty-Method and the Augmented-Lagrange-Method, which are analyzed with respect to their computational robustness

Challenges of continuum robots in clinical context: a review

With the maturity of surgical robotic systems based on traditional rigid-link principles, the rate of progress slowed as limits of size and controllable degrees of freedom were reached. Continuum robots came with the potential to deliver a step change in the next generation of medical devices, by providing better access, safer interactions and making new procedures possible. Over the last few years, several continuum robotic systems have been launched commercially and have been increasingly adopted in hospitals. Despite the clear progress achieved, continuum robots still suffer from design complexity hindering their dexterity and scalability. Recent advances in actuation methods have looked to address this issue, offering alternatives to commonly employed approaches. Additionally, continuum structures introduce significant complexity in modelling, sensing, control and fabrication; topics which are of particular focus in the robotics community. It is, therefore, the aim of the presented work to highlight the pertinent areas of active research and to discuss the challenges to be addressed before the potential of continuum robots as medical devices may be fully realised

Cardiovascular Magnetic Resonance Imaging for the Investigation of Ischaemic Heart Disease

Introduction: Coronary artery disease (CAD) remains the number one cause of mortality worldwide; improving diagnosis and treatment is a priority. Multi- parametric cardiovascular magnetic resonance (CMR) offers quantitative assessment of the cardiovascular system with a variety of techniques allowing assessment of anatomy, function, myocardial composition and perfusion during a single scan. Aims: To assess 1.) diagnostic accuracy of visual and quantitative perfusion CMR to single-photon emission computed tomography (MPS-SPECT) in patients with left main stem CAD. 2.) the hypothesis that patients with ischaemic (ICM) and non-ischaemic cardiomyopathy (NICM) have different torsion and strain parameters 3.) development and validation of a contemporary multivariable risk model of CAD from a large population undergoing X-ray angiography. 4.) a rapid 3D mDIXON pulse sequence for image quality and quantitation of MI. 5.) T1 rho prepared (T1ρ) dark blood sequence and compare to blood nulled PSIR (BN) and standard myocardium nulled PSIR (MN) for detection and quantification of scar. Methods: Patients were recruited between 2008 and 2017. Patients in chapters 3,4,6,7 underwent multi-parametric CMR including late gadolinium enhancement (LGE) imaging at 1.5 or 3.0T. Patients in chapter 5 underwent angiography. Results: 1.) CMR demonstrated significantly higher area under the curve for detection of LMS or equivalent disease over MPS-SPECT(P=0.0001). 2.) Despite no difference in LV dimensions, EF and strain between ICM and NICM, NICM patients had significantly lower LV twist(P=0.023) and torsion(P=0.017) compared to ICM. 3.) The developed model discriminated well and was well-calibrated. Diamond and Forrester and Duke scores substantially over-predicted CAD risk, whilst CAD Consortium risk models slightly under-estimated risk. 4.) Image quality was comparable between 3D and 2D LGE(P=0.162). Time for 3D image acquisition was only 5% of the time required for a standard 2D acquisition. 5.) CNRscar-blood was significantly increased for BN and T1ρ compared to MN LGE. BN LGE demonstrated significantly higher reader confidence scores

Atherosclerosis: Methods and Protocols

This volume provides detailed, up-to-date methods used in research on Atherosclerosis. Chapters guide readers through an overview of the pathogenesis of atherosclerosis and model systems together with in vitro, ex vivo, in vivo and emerging methods in atherosclerosis research. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Atherosclerosis: Methods and Protocols serves as an invaluable resource for those engaging in research on atherosclerosis and cardiovascular disease, as well as for researchers who are new to t