5,154 research outputs found
Superiorization and Perturbation Resilience of Algorithms: A Continuously Updated Bibliography
This document presents a, (mostly) chronologically ordered, bibliography of
scientific publications on the superiorization methodology and perturbation
resilience of algorithms which is compiled and continuously updated by us at:
http://math.haifa.ac.il/yair/bib-superiorization-censor.html. Since the
beginings of this topic we try to trace the work that has been published about
it since its inception. To the best of our knowledge this bibliography
represents all available publications on this topic to date, and while the URL
is continuously updated we will revise this document and bring it up to date on
arXiv approximately once a year. Abstracts of the cited works, and some links
and downloadable files of preprints or reprints are available on the above
mentioned Internet page. If you know of a related scientific work in any form
that should be included here kindly write to me on: [email protected] with
full bibliographic details, a DOI if available, and a PDF copy of the work if
possible. The Internet page was initiated on March 7, 2015, and has been last
updated on March 12, 2020.Comment: Original report: June 13, 2015 contained 41 items. First revision:
March 9, 2017 contained 64 items. Second revision: March 8, 2018 contained 76
items. Third revision: March 11, 2019 contains 90 items. Fourth revision:
March 16, 2020 contains 112 item
Focal Spot, Summer 1986
https://digitalcommons.wustl.edu/focal_spot_archives/1043/thumbnail.jp
Neuromyths for educational research and the educational field
status: publishe
Guest Editorial Special Issue on Medical Imaging and Image Computing in Computational Physiology
International audienceThe January 2013 Special Issue of IEEE transactions on medical imaging discusses papers on medical imaging and image computing in computational physiology. Aslanid and co-researchers present an experimental technique based on stained micro computed tomography (CT) images to construct very detailed atrial models of the canine heart. The paper by Sebastian proposes a model of the cardiac conduction system (CCS) based on structural information derived from stained calf tissue. Ho, Mithraratne and Hunter present a numerical simulation of detailed cerebral venous flow. The third category of papers deals with computational methods for simulating medical imagery and incorporate knowledge of imaging physics and physiology/biophysics. The work by Morales showed how the combination of device modeling and virtual deployment, in addition to patient-specific image-based anatomical modeling, can help to carry out patient-specific treatment plans and assess alternative therapeutic strategies
Introduction to the ACTA IMEKO issue devoted to selected papers presented in the 14th Joint International IMEKO TC1 + TC7 + TC13 Symposium
This editorial article is a brief introduction to the ACTA IMEKO issue devoted to selected papers presented in the 14th Joint International IMEKO TC1 + TC7 + TC13 Symposium "Intelligent Quality Measurements - Theory, Education and Training". This Symposium took place in Jena, Germany from August 31st to September 2nd 2011 in conjunction with the 56th IWK Ilmenau University of Technology and the 11th SpectroNet Collaboration Forum
From Nano to Macro: Overview of the IEEE Bio Image and Signal Processing Technical Committee
The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the
IEEE Signal Processing Society (SPS) promotes activities within the broad
technical field of biomedical image and signal processing. Areas of interest
include medical and biological imaging, digital pathology, molecular imaging,
microscopy, and associated computational imaging, image analysis, and
image-guided treatment, alongside physiological signal processing,
computational biology, and bioinformatics. BISP has 40 members and covers a
wide range of EDICS, including CIS-MI: Medical Imaging, BIO-MIA: Medical Image
Analysis, BIO-BI: Biological Imaging, BIO: Biomedical Signal Processing,
BIO-BCI: Brain/Human-Computer Interfaces, and BIO-INFR: Bioinformatics. BISP
plays a central role in the organization of the IEEE International Symposium on
Biomedical Imaging (ISBI) and contributes to the technical sessions at the IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP),
and the IEEE International Conference on Image Processing (ICIP). In this
paper, we provide a brief history of the TC, review the technological and
methodological contributions its community delivered, and highlight promising
new directions we anticipate
Bioinformatics and Medicine in the Era of Deep Learning
Many of the current scientific advances in the life sciences have their
origin in the intensive use of data for knowledge discovery. In no area this is
so clear as in bioinformatics, led by technological breakthroughs in data
acquisition technologies. It has been argued that bioinformatics could quickly
become the field of research generating the largest data repositories, beating
other data-intensive areas such as high-energy physics or astroinformatics.
Over the last decade, deep learning has become a disruptive advance in machine
learning, giving new live to the long-standing connectionist paradigm in
artificial intelligence. Deep learning methods are ideally suited to
large-scale data and, therefore, they should be ideally suited to knowledge
discovery in bioinformatics and biomedicine at large. In this brief paper, we
review key aspects of the application of deep learning in bioinformatics and
medicine, drawing from the themes covered by the contributions to an ESANN 2018
special session devoted to this topic
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