Significant medical image compression techniques: a review

Telemedicine applications allow the patient and doctor to communicate with each other through network services. Several medical image compression techniques have been suggested by researchers in the past years. This review paper offers a comparison of the algorithms and the performance by analysing three factors that influence the choice of compression algorithm, which are image quality, compression ratio, and compression speed. The results of previous research have shown that there is a need for effective algorithms for medical imaging without data loss, which is why the lossless compression process is used to compress medical records. Lossless compression, however, has minimal compression ratio efficiency. The way to get the optimum compression ratio is by segmentation of the image into region of interest (ROI) and non-ROI zones, where the power and time needed can be minimised due to the smaller scale. Recently, several researchers have been attempting to create hybrid compression algorithms by integrating different compression techniques to increase the efficiency of compression algorithms

Medical imaging analysis with artificial neural networks

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging

High resolution optical analysis of Nav1.6 localization and trafficking

2015 Summer.Voltage-gated sodium (Naᵥ) channels are responsible for the depolarizing phase of the action potential in most nerve cell membranes. As such, these proteins are essential for nearly all functions of the nervous system including thought, movement, sensation, and many other basic physiological processes. Neurons precisely control the number, type, and location of these important ion channels. The density of Naᵥ channels within the axon initial segment (AIS) of neurons can be more than 35-fold greater than that in the somatodendritic region and this localization is vital to action potential initiation. Dysfunction or mislocalization of Naᵥ channels is linked to many diseases including epilepsy, cardiac arrhythmias, and pain disorders. Despite the importance of Naᵥ channels, knowledge of their trafficking and cell-surface dynamics is severely limited. Research in this area has been hampered by the lack of modified Naᵥ constructs suitable for investigations into neuronal Naᵥ cell biology. This dissertation demonstrates the successful creation of modified Naᵥ1.6 cDNAs that retain wild-type function and trafficking following expression in cultured rat hippocampal neurons. The Naᵥ1.6 isoform is emphasized because it 1) is the most abundant Naᵥ channel in the mammalian brain, 2) is involved in setting the action potential threshold, 3) controls repetitive firing in Purkinje neurons and retinal ganglion cells, 4) and can contain mutations causing epilepsy, ataxia, or mental retardation. Using single-molecule microscopy techniques, the trafficking and cell-surface dynamics of Naᵥ1.6 were investigated. In contrast to the current dogma that Naᵥ channels are localized to the AIS of neurons through diffusion trapping and selective endocytosis, the experiments presented here demonstrate that Naᵥ1.6 is directly delivered to the AIS via a vesicular delivery mechanism. The modified Naᵥ1.6 constructs were also used to investigate the distribution and cell-surface dynamics of Naᵥ1.6. Somatic Naᵥ1.6 channels were observed to localize to small membrane regions, or nanoclusters, and this localization is ankyrinG independent. These sites, which could represent sites of localized channel regulation, represent a new Naᵥ localization mechanism. Channels within the nanoclusters appear to be stably bound on the order of minutes to hours, while non-clustered Naᵥ1.6 channels are mobile. Novel single-particle tracking photoactivation localization microscopy (spt-PALM) analysis of Naᵥ1.6-Dendra2 demonstrated that the nanoclusters can be modeled as energy wells and the depth of these interactions increase with neuronal age. The research presented in this dissertation represents the first single-molecule approaches to any Naᵥ channel isoform. The approaches developed during the course of this dissertation research will further our understanding of Naᵥ1.6 cell biology under both normal and pathological conditions

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

Fluid Dynamics Characterization of Transcatheter Aortic Valves

Aortic stenosis due to degenerative calcific aortic valvular disease is the most reason for aortic valve replacement in developed countries. Aortic stenosis affects up to 7% of the world population, and current clinical data indicate that the number of the affected people could be triple by 2050, due to population ageing and health lifestyle. Transcatheter aortic valve replacement (TAVR) was introduced as a minimal invasive treatment of severe aortic stenosis. Even though surgical aortic valve replacement (SAVR) is considered the golden standard treatment for severe aortic stenosis patients, TAVR showed equivalent or even superior outcome compare to SAVR. Currently, transcatheter aortic valves (TAVs) have limited clinical data in term of fluid dynamics performance of TAVs, in contrast to surgical aortic valves (SAVs). Due to limitations associated with devices that are used to evaluate the performance of TAVs in patients such as echocardiography, magnetic response imaging (MRI) and an accurate method to detect and evaluate any leakage. Thus, an experimental testing and computational modeling were performed to compare the performance of TAVs to SAVs in term of hemodynamic performance and addressing some clinical complications that are associated with TAV devices. Therefore, the objectives of this dissertation were to used particle image velocimetry (PIV) to obtain velocity and shear stress contours to indicate any damage to blood elements that could lead to stroke. Additionally, investigate the cause of reduced TAV leaflets motion post-TAVR procedure using blood residence time (BRT) approach. Furthermore, validating the current guideline uses to evaluate paravalvular leakage (PVL) severity and develop a new methodology to assess and evaluate the severity of PVL post-TAVR based on fluid dynamics. Moreover, developing and validating non-invasive procedure to estimate energy loss post-TAVR during the cardiac cycle and determine the workload imposes on the left ventricular. Thus, the main goal of this dissertation was to develop experimental testing to measure hemodynamics performance of TAVs and validating computational modeling output in term of flow field

Suffolk University Undergraduate Academic Catalog, College of Arts and Sciences and Sawyer Business School, 2013-2014

This catalog contains information for the undergraduate programs in the College of Arts and Sciences and the Sawyer Business School. The catalog is a pdf version of the Suffolk website, so many pages have repeated information and links in the document will not work. The catalog is keyword searchable by clicking ctrl+f. A-Z course descriptions are also included here as separate pdf files with lists of CAS and SBS courses. Please contact the Archives if you need assistance navigating this catalog or finding information on degree requirements or course descriptions.https://dc.suffolk.edu/cassbs-catalogs/1166/thumbnail.jp

Suffolk University Academic Catalog, College of Arts and Sciences and Sawyer Business School, 2022-2023

This catalog contains information for both the undergraduate and graduate programs in the College of Arts and Sciences and the Sawyer Business School.https://dc.suffolk.edu/cassbs-catalogs/1184/thumbnail.jp