Single-Photon Emission Computed Tomography (SPECT) left ventricular assessment protocols are important for detecting ischemia in high-risk patients. To quantitatively measure myocardial function, clinicians depend on commercially available solutions to segment and reorient the left ventricle (LV) for evaluation. Based on large normal datasets, the segmentation performance and the high price of these solutions can hinder the availability of reliable and precise localization of the LV delineation. To overcome the aforementioned shortcomings this paper aims to give a recipe for diagnostic centers as well as for clinics to automatically segment the myocardium based on small and low-quality labels on reconstructed SPECT, complete field-of-view (FOV) volumes. A combination of Continuous Max-Flow (CMF) with prior shape information is developed to augment the 3D U-Net self-supervised learning (SSL) approach on various geometries of SPECT apparatus. Experimental results on the acquired dataset have shown a 5-10\% increase in quantitative metrics based on the previous State-of-the-Art (SOTA) solutions, suggesting a good plausible way to tackle the few-shot SSL problem on high-noise SPECT cardiac datasets.

Think Stats: Probability and Statistics for Programmers by Allen Downey.

Full episode with Gilbert Strang (Nov 2019): https://www.youtube.com/watch?v lEZPf... Subscribe to this channel if you like clips and to the main channel if you like full length episodes: https://www.youtube.com/lexfridman Gilbert Strang is a professor of mathematics at MIT and perhaps one of the most famous and impactful teachers of math in the world. His MIT OpenCourseWare lectures on linear algebra have been viewed millions of times. Subscribe to this YouTube channel or connect on: - Twitter: https://twitter.com/lexfridman

Gilbert Strang is a professor of mathematics at MIT and perhaps one of the most famous and impactful teachers of math in the world. His MIT OpenCourseWare lectures on linear algebra have been viewed millions of times. This conversation is part of the Artificial Intelligence podcast.

Reviewed by Douglas Farenick, University of Regina Undergraduate mathematics textbooks are not what they used to be, and Gilbert Strang's superb new edition of Introduction to Linear Algebra is an example of everything that a modern textbook could possibly be, and more. First, let us consider the book itself. As with his classic Linear Algebra and its Applications (Academic Press) from forty years ago, Strang's new edition of Introduction to Linear Algebra keeps one eye on the theory, the other on applications, and has thestated goal of "opening linear algebra to the world" (Preface, page x).Aimed at the serious undergraduate student - though not just thoseundergraduates who fill the lecture halls of MIT, Strang's homeinstitution - the writing is engaging and personal, and the presentation is exceptionally clear and informative (even seasoned instructors maybenefit from Strang's insights). The first six chapters offer atraditional first course that covers vector algebra and geometry,systems of linear equations, vector spaces and subspaces, orthogonality, determinants, and eigenvalues and eigenvectors. The next three chapters are devoted to the singular value decomposition, lineartransformations, and complex numbers and complex matrices, followed bychapters that address a wide range of contemporary applications andcomputational issues. The book concludes with a brief but cogenttreatment of linear statistical analysis. I would like to stress that there is arichness to the material that goes beyond most texts at this level.Included are guides to websites and to OpenCourseWare, which I shallcomment upon later in this review.

Concepts in the book are laid out clearly, often with diagrams, but the book moves quickly. The book expects you to keep up or you will fall behind. That being said, each section has an overview of the concepts to be covered and ends with worked examples and quiz questions, the answers to which are available on the book's website. Take my free 7-day email crash course now (with sample code). Click to sign-up and also get a free PDF Ebook version of the course.