Machine Learning/Deep Learning in Medical Image Processing

Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL). This special issue, “Machine Learning/Deep Learning in Medical Image Processing”, has been launched to provide an opportunity for researchers in the area of medical image processing to highlight recent developments made in their fields with ML/DL. Seven excellent papers that cover a wide variety of medical/clinical aspects are selected in this special issue

Improved graph cut model with features of superpixels and neighborhood patches for myocardium segmentation from ultrasound image

Ultrasound (US) imaging has the technical advantages for the functional evaluation of myocardium compared with other imaging modalities. However, it is a challenge of extracting the myocardial tissues from the background due to low quality of US imaging. To better extract the myocardial tissues, this study proposes a semi-supervised segmentation method of fast Superpixels and Neighborhood Patches based Continuous Min-Cut (fSP-CMC). The US image is represented by a graph, which is constructed depending on the features of superpixels and neighborhood patches

Echocardiography

The book "Echocardiography - New Techniques" brings worldwide contributions from highly acclaimed clinical and imaging science investigators, and representatives from academic medical centers. Each chapter is designed and written to be accessible to those with a basic knowledge of echocardiography. Additionally, the chapters are meant to be stimulating and educational to the experts and investigators in the field of echocardiography. This book is aimed primarily at cardiology fellows on their basic echocardiography rotation, fellows in general internal medicine, radiology and emergency medicine, and experts in the arena of echocardiography. Over the last few decades, the rate of technological advancements has developed dramatically, resulting in new techniques and improved echocardiographic imaging. The authors of this book focused on presenting the most advanced techniques useful in today's research and in daily clinical practice. These advanced techniques are utilized in the detection of different cardiac pathologies in patients, in contributing to their clinical decision, as well as follow-up and outcome predictions. In addition to the advanced techniques covered, this book expounds upon several special pathologies with respect to the functions of echocardiography

Measurements of Pre-Clinical Liver Perfusion Using Arterial Spin Labelling MRI

Magnetic Resonance Imaging (MRI) has been at the focus of medical research as its availability and fidelity has improved in the last thirty years. MRI offers both high spatial resolution and excellent soft tissue contrast compared to complimentary medical imaging techniques, without the need to expose patients to ionising radiation. Novel MRI methods that utilise the intrinsic body water signal are still being developed and refined. Arterial Spin Labelling (ASL) MRI provides a non-invasive method to measure tissue perfusion, which has been extensively applied in the brain, and demonstrated pre-clinically in the heart and kidneys. However, there is currently no literature reporting the development and use pre-clinical liver ASL – possibly due to complex methodology and quantification necessary in small animals. Clinical liver perfusion imaging is predominantly carried out using an injected Gadolinium-based contrast agent; this technique can be challenging to quantify, cannot be immediately re-administered and may have complications for patients with renal impairment. A methodology to measure liver perfusion without the need for a contrast agent would find utility in a number of different hepatic diseases; monitoring pathophysiology and therapy efficacy. This research investigates the feasibility of a pre-clinical measure of liver perfusion using ASL and its potential application to a pre-clinical model of hepatic disease. We aim to apply the method to monitor novel therapy efficacy in pre-clinical disease models, to eventually translate both therapy and hepatic ASL into the clinical environment

Development of MRI Techniques for Experimental Models of Cardiovascular Disease

Cardiovascular diseases (CVDs) – including stroke and heart failure – are the leading cause of death worldwide. More people die from CVDs each year than any other cause. Magnetic resonance imaging (MRI) is a powerful technique which is now routinely used for imaging these diseases as it offers high-resolution anatomical detail, exquisite soft-tissue contrast and assessment of function such as tissue water content, oxygenation, metabolism, vascular blood flow and microvascular perfusion. This thesis focuses on the development of MRI techniques for use in pre-clinical animal models of cardiovascular diseases, with a focus on stroke and heart disease. Firstly, in chapter 3, the continued development of an in-house MRI sequence known as extravascular convectography (EVAC) for measuring the flow of interstitial fluid is described. A series of phantom experiments were conducted to assess the sensitivity of the sequence to slow flowing fluid. Next, an in vivo repeatability and reproducibility study was conducted before finally the technique was applied to a rat model of stroke. In chapter 4, a pair of studies was carried out using recently established, advanced cardiac imaging techniques. In the first study, CINE and late gadolinium-enhanced inversion recovery (LGE IR) imaging were used to assess cardiac structure and function in a Prox1-deficient genetic mouse model of dilated cardiomyopathy. In the second part of the chapter, a multi-parametric MRI study – incorporating CINE, LGE IR, arterial spin labeling and T2-mapping – was conducted in a mouse model of reperfused myocardial infarction to assess the extent of area-at-risk and compare with gold-standard histological staining. Finally, in chapter 5, the development of a retrospective high-temporal resolution (HTR) CINE MRI sequence for assessing cardiac diastolic function is described and compared with pulsed wave Doppler ultrasound, which is the currently-accepted standard for measuring diastolic function. The HTR-CINE sequence was established, validated and optimised in phantoms and naïve mouse hearts. Repeatability studies were then carried out to ensure the robustness of the technique before application to a mouse model of myocardial infarction. The overall aim of the research in this thesis is the development of MRI techniques for application to experimental models of cardiovascular disease

Non-invasive ultrasound monitoring of regional carotid wall structure and deformation in atherosclerosis

Thesis (Ph. D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 2001.Includes bibliographical references (p. 223-242).Atherosclerosis is characterized by local remodeling of arterial structure and distensibility. Developing lesions either progress gradually to compromise tissue perfusion or rupture suddenly to cause catastrophic myocardial infarction or stroke. Reliable measurement of changes in arterial structure and composition is required for assessment of disease progression. Non-invasive carotid ultrasound can image the heterogeneity of wall structure and distensibility caused by atherosclerosis. However, this capability has not been utilized for clinical monitoring because of speckle noise and other artifacts. Clinical measures focus instead on average wall thickness and diameter distension in the distal common carotid to reduce sensitivity to noise. The goal of our research was to develop an effective system for reliable regional structure and deformation measurements since these are more sensitive indicators of disease progression. We constructed a system for freehand ultrasound scanning based on custom software which simultaneously acquires real-time image sequences and 3D frame localization data from an electromagnetic spatial localizer. With finite element modeling, we evaluated candidate measures of regional wall deformation.(cont.) Finally, we developed a multi-step scheme for robust estimation of local wall structure and deformation. This new strategy is based on a directionally-sensitive segmentation functional and a motion-region-of-interest constrained optical flow algorithm. We validated this estimator with simulated images and clinical ultrasound data. The results show structure estimates that are accurate and precise, with inter- and intra-observer reproducibility surpassing existing methods. Estimates of wall velocity and deformation likewise show good overall accuracy and precision. We present results from a proof-of-principle evaluation conducted in a pilot study of normal subjects and clinical patients. For one example, we demonstrate the combination of 2D image processing with 3D frame localization for visualization of the carotid volume. With slice localization, estimates of carotid wall structure and deformation can be derived for all axial positions along the carotid artery. The elements developed here provide the tools necessary for reliable quantification of regional wall structure and composition changes which result from atherosclerosis.by Raymond C. Chan.Ph.D