Results for 'Medical imaging'

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  1.  7
    Philosophy of Advanced Medical Imaging.Elisabetta Lalumera & Stefano Fanti - 2021 - Springer International.
    This is the first book to explore the epistemology and ethics of advanced imaging tests, in order to improve the critical understanding of the nature of knowledge they provide and the practical consequences of their utilization in healthcare. Advanced medical imaging tests, such as PET and MRI, have gained center stage in medical research and in patients’ care. They also increasingly raise questions that pertain to philosophy: What is required to be an expert in reading images? (...)
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  2.  8
    Medical Image Segmentation Algorithm Based on Optimized Convolutional Neural Network-Adaptive Dropout Depth Calculation.Feng-Ping An & Jun-E. Liu - 2020 - Complexity 2020:1-13.
    Medical image segmentation is a key technology for image guidance. Therefore, the advantages and disadvantages of image segmentation play an important role in image-guided surgery. Traditional machine learning methods have achieved certain beneficial effects in medical image segmentation, but they have problems such as low classification accuracy and poor robustness. Deep learning theory has good generalizability and feature extraction ability, which provides a new idea for solving medical image segmentation problems. However, deep learning has problems in terms (...)
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  3.  39
    Gestalt Descriptions Embodiments and Medical Image Interpretation.Jan Kyrre Berg Olsen Friis - 2017 - AI and Society 32 (2):209-218.
    In this paper I will argue that medical specialists interpret and diagnose through technological mediations like X-ray and fMRI images, and by actualizing embodied skills tacitly they are determining the identity of objects in the perceptual field. The initial phase of human interpretation of visual objects takes place during the moments of visual perception before we are consciously aware of the perceived. What facilitate this innate ability to interpret are experiences, learning and training that become humanly embodied skills. These (...)
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  4.  38
    Medical Imaging: Pictures, “as If” and the Power of Evidence. [REVIEW]Irmgard Müller & Heiner Fangerau - 2010 - Medicine Studies 2 (3):151-160.
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  5. Improving Medical Image Decision‐Making by Leveraging Metacognitive Processes and Representational Similarity.Eeshan Hasan, Quentin Eichbaum, Adam C. Seegmiller, Charles Stratton & Jennifer S. Trueblood - 2022 - Topics in Cognitive Science 14 (2):400-413.
    Topics in Cognitive Science, Volume 14, Issue 2, Page 400-413, April 2022.
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  6. The Role of Medical Imaging in the Abortion Debate.D. Kirklin - 2004 - Journal of Medical Ethics 30 (5):426-426.
    Deborah Kirklin discusses the role of medical imaging in the abortion debateThe latest developments in fetal ultrasound technology, made public by a group called Create,1 and first introduced to the wider UK public by the Evening Standard newspaper reporter Isabel Oakeshott in September 2003 and again in July 2004, have evoked a flood of responses from the public, pro-life and pro-choice campaigners, and politicians, re-igniting the debate about abortion in the UK and elsewhere. The focus of the Evening (...)
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  7.  6
    Editorial: Medical Image Perception: How Much Do We Understand It?Tim Donovan, Damien Litchfield & Trevor J. Crawford - 2017 - Frontiers in Psychology 8.
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  8.  24
    The Body in Medical Imaging Between Reality and Construction.Britta Schinzel - 2006 - Poiesis and Praxis 4 (3):185-198.
    Medical imaging has provided insight into the living body that were not possible beforehand. With these methods a revolution in medical diagnosis and biomedical research has begun. Problematic aspects on the other hand are arising from the highly constructive properties of image production, which use complicated physical and physiological effects. Images are established via highly complicated combinations of technology and contingently chosen mathematical and algorithmic solutions. In addition, image construction follows properties of the human visual and cognitive (...)
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  9.  14
    Entities and Relations in Medical Imaging: An Analysis of Computed Tomography Reporting.Dirk Marwede & James Matthew Fielding - 2007 - Applied Ontology 2 (1):67-79.
  10.  12
    Enhancement of Medical Image Details Via Wavelet Homomorphic Filtering Transform.Chao Li, Huixian Duan, Guangyao Li & Yunlan Tan - 2014 - Journal of Intelligent Systems 23 (1):83-94.
    A new medical image enhancement algorithm based on spatial frequency domain is presented in this article. The medical image is first divided into several sub-images based on dyadic wavelet scale analysis. At each level, different directional sub-band images can reflect the different characteristics of the image. A low-frequency sub-band image maintains the original image content information, and high-frequency sub-band images represent image details such as edges and regional boundaries. The corresponding sub-band images are then enhanced by different Butterworth (...)
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  11.  1
    Reproduction Inside/Outside: Medical Imaging and the Domestication of Assisted Reproductive Technologies.Merete Lie - 2015 - European Journal of Women's Studies 22 (1):53-69.
    Contemporary medical imaging technologies produce images on the level of human cells. As a result of such images, egg and sperm cells have become well-known artefacts of popular culture. Medical imaging technology has transformed these gametes from invisible matter integrated in biological processes within the body to identifiable objects. The visualisation of egg and sperm cells has literally lifted the process of human reproduction out of the female body and made the gametes appear as protagonists in (...)
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  12.  2
    A Blind Medical Image Watermarking for Secure E-Healthcare Application Using Crypto-Watermarking System.Polurie Venkata Vijay Kishore & Puvvadi Aparna - 2019 - Journal of Intelligent Systems 29 (1):1558-1575.
    A reliable medical image management must provide proper security for patient information. Protecting the medical information of the patients is a major concern in all hospitals. Digital watermarking is a procedure prevalently used to secure the confidentiality of medical information and maintain them, which upgrades patient health awareness. To protect the medical information, the robust and lossless patient medical information sharing system using crypto-watermarking method is proposed. The proposed system consists of two phases: embedding and (...)
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  13. Naked to the Bone: Medical Imaging in the Twentieth Century. Bettyann Holtzmann Kevles.Lisa Cartwright - 1997 - Isis 88 (4):738-739.
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  14. The Evolution of Medical Imaging: From Geiger Counters to MRI--A Personal Saga.John R. Mallard - 2003 - Perspectives in Biology and Medicine 46 (3):349-370.
  15.  7
    Multi-Modal Medical Images Registration Using Differential Geometry and the Hausdorff Distance.Fahad Hameed Ahmad & Sudha Natarajan - 2010 - Journal of Intelligent Systems 19 (4):363-377.
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  16.  12
    Neural Expert Systems in Medical Image Interpretation: Development, Use, and Ethical Issues.Athanasia Pouloudi & George D. Magoulas - 2000 - Journal of Intelligent Systems 10 (5-6):451-472.
  17.  4
    Vascular Section Estimation in Medical Images Using Combined Feature Detection and Evolutionary Optimization.Iván Macía & Manuel Graña - 2012 - In Emilio Corchado, Vaclav Snasel, Ajith Abraham, Michał Woźniak, Manuel Grana & Sung-Bae Cho (eds.), Hybrid Artificial Intelligent Systems. Springer. pp. 503--513.
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  18.  4
    Origins and Development of Medical Imaging. T. Doby, G. Alker.Bettyann Holtzmann Kevles - 1997 - Isis 88 (4):739-739.
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  19.  12
    An Overview of Segmentation Algorithms for the Analysis of Anomalies on Medical Images.Subbiahpillai Neelakantapillai Kumar, Alfred Lenin Fred & Paul Sebastin Varghese - 2019 - Journal of Intelligent Systems 29 (1):612-625.
    Human disease identification from the scanned body parts helps medical practitioners make the right decision in lesser time. Image segmentation plays a vital role in automated diagnosis for the delineation of anatomical organs and anomalies. There are many variants of segmentation algorithms used by current researchers, whereas there is no universal algorithm for all medical images. This paper classifies some of the widely used medical image segmentation algorithms based on their evolution, and the features of each generation (...)
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  20.  7
    The Holistic Processing Account of Visual Expertise in Medical Image Perception: A Review.Heather Sheridan & Eyal M. Reingold - 2017 - Frontiers in Psychology 8.
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  21.  1
    An Intelligent Medical Imaging Approach for Various Blood Structure Classifications.Madallah Alruwaili - 2021 - Complexity 2021:1-10.
    Blood is a vital body fluid and can be instrumental in identifying various pathological conditions. Nowadays, a lot of people are suffering from COVID-19 and every country has its own limited testing capacity. Consequently, a system is required to help doctors analyze a patient’s blood structure including COVID-19. Therefore, in this paper, we extracted and selected blood features by proposing a new feature extraction and selection method named stepwise linear discriminant analysis. SWLDA emphasizes on picking confined features from blood structure (...)
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  22.  3
    Disentangling Prevalence Induced Biases in Medical Image Decision-Making.Jennifer S. Trueblood, Quentin Eichbaum, Adam C. Seegmiller, Charles Stratton, Payton O'Daniels & William R. Holmes - 2021 - Cognition 212:104713.
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  23. Media Retrieval-Cross-Modal Interaction and Integration with Relevance Feedback for Medical Image Retrieval.Md Mahmudur Rahman, Varun Sood, Bipin C. Desai & Prabir Bhattacharya - 2006 - In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer Verlag. pp. 440-449.
  24. Feature Visibility and Detectability in Medical Images.Rg Swensson, Se Seltzer, Pf Judy, R. Nawfel & I. Kazda - 1989 - Bulletin of the Psychonomic Society 27 (6):526-526.
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  25. Modeling Detection and Localization in Medical Images.Rg Swensson & Pf Judy - 1990 - Bulletin of the Psychonomic Society 28 (6):487-488.
     
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  26.  38
    Heiner Fangerau, Rethy Chhem, Irmgard Müller and Shih-Chang Wang , Medical Imaging and Philosophy: Challenges, Reflections and Actions. Stuttgart: Franz Steiner Verlag, 2012. Pp. 190. ISBN 978-3-515-10046-5. €38.00. [REVIEW]Norberto Serpente - 2014 - British Journal for the History of Science 47 (3):581-583.
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  27. Predicting Visual Search Accuracy in Symbolic Displays and Medical Images.M. P. Eckstein, J. P. Thomas & J. S. Whiting - 1996 - In Enrique Villanueva (ed.), Perception. Ridgeview. pp. 5-5.
  28.  9
    Heiner Fangerau;, Rethy Chhem;, Irmgard Müller;, Shih-Chang Wang . Medical Imaging and Philosophy: Challenges, Reflections, Actions. 190 Pp., Illus. Stuttgart: Franz Steiner Verlag, 2012. €38. [REVIEW]Louise Whiteley - 2013 - Isis 104 (4):820-821.
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  29.  1
    What We Do and Do Not Know About Teaching Medical Image Interpretation.Ellen M. Kok, Koos van Geel, Jeroen J. G. van Merriënboer & Simon G. F. Robben - 2017 - Frontiers in Psychology 8.
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  30.  3
    José van Dijck. The Transparent Body: A Cultural Analysis of Medical Imaging. Xii + 193 Pp., Illus., Bibl., Index. Seattle: University of Washington Press, 2005. $24.95. [REVIEW]David Serlin - 2006 - Isis 97 (4):804-804.
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  31.  1
    A Qualitative Study Exploring the Experience of Viewing Three‐Dimensional Medical Images During an Orthopaedic Outpatient Consultation From the Perspective of Patients, Health Care Professionals, and Lay Representatives.Emma E. Phelps, Richard Wellings, Melina Kunar, Charles Hutchinson & Frances Griffiths - 2021 - Journal of Evaluation in Clinical Practice 27 (2):333-343.
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  32.  6
    Images as Catalysts for Meaning-Making in Medical Pain Encounters: A Multidisciplinary Analysis.Deborah Padfield, Helen Omand, Elena Semino, Amanda C. De C. Williams & Joanna M. Zakrzewska - 2018 - Medical Humanities 44 (2):74-81.
    The challenge for those treating or witnessing pain is to find a way of crossing the chasm of meaning between them and the person living with pain. This paper proposes that images can strengthen agency in the person with pain, particularly but not only in the clinical setting, and can create a shared space within which to negotiate meaning. It draws on multidisciplinary analyses of unique material resulting from two fine art/medical collaborations in London, UK, in which the invisible (...)
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  33. The Physician's Covenant: Images of the Healer in Medical Ethics.William F. May - 1983 - Westminster John Knox Press.
    A discussion of Christian ethics focuses on the physician's image as a parent, warrior against death, expert, and teacher, and the oath that guides his or her practice.
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  34.  16
    Clinical Image Consent Requirements: Variability Among Top Ten Medical Journals.Juan N. Lessing, Nicholas M. Mark, Matthew K. Wynia & Ethan Cumbler - 2019 - Journal of Academic Ethics 17 (4):423-427.
    The consent process for publication of clinical images in medical journals varies widely. The extent of this variation is not known. It is also not known whether journals follow their own stated best practices or the guidance of the International Committee of Medical Journal Editors. We assessed consent requirements in a sample of 10 top impact factor general medicine journals that publish clinical images, examining variability in consent requirements for clinical image publication and congruence of requirements with the (...)
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  35.  67
    Reliability of Molecular Imaging Diagnostics.Elisabetta Lalumera, Stefano Fanti & Giovanni Boniolo - 2021 - Synthese (S23):5701-5717.
    Advanced medical imaging, such as CT, fMRI and PET, has undergone enormous progress in recent years, both in accuracy and utilization. Such techniques often bring with them an illusion of immediacy, the idea that the body and its diseases can be directly inspected. In this paper we target this illusion and address the issue of the reliability of advanced imaging tests as knowledge procedures, taking positron emission tomography in oncology as paradigmatic case study. After individuating a suitable (...)
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  36.  5
    Images of Psychoanalysis: A Phenomenological Study of Medical Students’ Sense of Psychoanalysis Before and After a Four-Week Elective Course.Maurice Apprey - 2016 - Indo-Pacific Journal of Phenomenology 16 (1-2):141-152.
    In concept, an image has both verticality and horizontal dimensions. Saturated images within this space have a horizon and can exceed that horizon. Within that horizon where the image dwells something chances itself upon the observer and the observed. Into that public space between self and other, students bring an instrumental approach to how they plan to deploy their new fund of knowledge, only to discover that the setting itself has become an event where surprise and upheaval disrupt their illusion (...)
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  37.  40
    Dimensions of Embodiment: Body Image and Body Schema in Medical Contexts.Shaun Gallagher - 2001 - In Kay Toombs (ed.), Handbook of Phenomenology and Medicine. Kluwer Academic Publishers. pp. 147--175.
  38.  12
    Digital Image Processing for Medical Applications.David R. Okada & Ron Blankstein - 2009 - Perspectives in Biology and Medicine 52 (4):617-623.
  39. Imaging Technology and the Philosophy of Causality.Jon Williamson - 2011 - Philosophy and Technology 24 (2):115-136.
    Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007) put forward the thesis that, at least in the health sciences, to establish the claim that C is a cause of E, one normally needs evidence of an underlying mechanism linking C and E as well as evidence that C makes a difference to E. This epistemological thesis poses a problem for most current analyses of causality which, in virtue of analysing causality in terms of just one of mechanisms or difference (...)
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  40.  2
    Radiography Image Analysis Using Cat Swarm Optimized Deep Belief Networks.Sura Khalil Abd, Mustafa Musa Jaber & Amer S. Elameer - 2021 - Journal of Intelligent Systems 31 (1):40-54.
    Radiography images are widely utilized in the health sector to recognize the patient health condition. The noise and irrelevant region information minimize the entire disease detection accuracy and computation complexity. Therefore, in this study, statistical Kolmogorov–Smirnov test has been integrated with wavelet transform to overcome the de-noising issues. Then the cat swarm-optimized deep belief network is applied to extract the features from the affected region. The optimized deep learning model reduces the feature training cost and time and improves the overall (...)
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  41.  4
    Bert Hansen. Picturing Medical Progress From Pasteur to Polio: A History of Mass Media Images and Popular Attitudes in America. Ix + 348 Pp., Illus., App., Index. Piscataway, N.J.: Rutgers University Press, 2009. $37.95. [REVIEW]Ludmilla Jordanova - 2010 - Isis 101 (4):896-897.
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  42.  26
    Imaging the Brain: Visualising “Pathological Entities”? Searching for Reliable Protocols Within Psychiatry and Their Impact on the Understanding of Psychiatric Diseases. [REVIEW]Lara Huber - 2008 - Poiesis and Praxis 6 (1-2):27-41.
    Given that visualisations via medical imaging have tremendously increased over the last decades, the overall presence of colour-coded brain slices generated on the basis of functional imaging, i.e. neuroimaging techniques, have led to the assumption of so-called kinds of brains or cognitive profiles that might be especially related to non-healthy humans affected by neurological, neuropsychological or psychiatric syndromes or disorders. In clinical contexts especially, one must consider that visualisations through medical imaging are suggestive in a (...)
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  43.  8
    An Efficient Technique for Three-Dimensional Image Visualization Through Two-Dimensional Images for Medical Data.Ganesan Gunasekaran & Meenakshisundaram Venkatesan - 2019 - Journal of Intelligent Systems 29 (1):100-109.
    The main idea behind this work is to present three-dimensional image visualization through two-dimensional images that comprise various images. 3D image visualization is one of the essential methods for excerpting data from given pieces. The main goal of this work is to figure out the outlines of the given 3D geometric primitives in each part, and then integrate these outlines or frames to reconstruct 3D geometric primitives. The proposed technique is very useful and can be applied to many kinds of (...)
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  44.  27
    Analogy and Difference: A Comparative Study of Medical and Astronomical Images in Books, 1470–1550.Isabelle Pantin - 2013 - Early Science and Medicine 18 (1-2):9-44.
    Medicine and astronomy were both scientific disciplines to which visual demonstration proved helpful, were taught in the universities, and were deeply influenced by humanism and by the development of print culture, but they did not use printed images in the same way. Thus, all the aspects of astronomical activity benefited from the accompaniment of printed images, whereas, even for anatomy, illustration does not seem to have been seen as a necessity in Renaissance medical books. To explore such a difference, (...)
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  45.  4
    Making Images/Making Bodies: Visibilizing and Disciplining Through Magnetic Resonance Imaging.Amit Prasad - 2005 - Science, Technology, and Human Values 30 (2):291-316.
    This article analyzes how the medical gaze made possible by MRI operates in radiological laboratories. It argues that although computer-assisted medical imaging technologies such as MRI shift radiological analysis to the realm of cyborg visuality, radiological analysis continues to depend on visualization produced by other technologies and diagnostic inputs. In the radiological laboratory, MRI is used to produce diverse sets of images of the internal parts of the body to zero in and visually extract the pathology. Visual (...)
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  46. Auxiliary Diagnosis Study of Integrated Electronic Medical Record Text and CT Images.Feng Yijie, Liu Kailin, Li Shi, Diao Hang & Duan Yuanchuan - 2022 - Journal of Intelligent Systems 31 (1):753-766.
    At present, most of the research in the field of medical-assisted diagnosis is carried out based on image or electronic medical records. Although there is some research foundation, they lack the comprehensive consideration of comprehensive image and text modes. Based on this situation, this article proposes a fusion classification auxiliary diagnosis model based on GoogleNet model and Bi-LSTM model, uses GoogleNet to process brain computed tomographic images of ischemic stroke patients and extract CT image features, uses Bi-LSTM model (...)
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  47.  8
    Impact of Visual Thinking Strategies (VTS) on the Analysis of Clinical Images: A Pre-Post Study of VTS in First-Year Medical Students.Gauri G. Agarwal, Meaghan McNulty, Katerina M. Santiago, Hope Torrents & Alberto J. Caban-Martinez - 2020 - Journal of Medical Humanities 41 (4):561-572.
    To assess the effectiveness of Visual Thinking Strategies in medical education curricula, a pretest–posttest experimental study design was used to evaluate the impact of participating in VTS workshops on first-year medical students. A total of forty-one intervention and sixty comparative students completed the study which included the analysis of clinical images followed by a measurement of word count, length of time analyzing images, and quality of written observations of clinical images. VTS training increased the total number of words (...)
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  48.  2
    Constructing the East–West Boundary: The Contested Place of a Modern Imaging Technology in South Korea’s Dual Medical System.Michael Lynch & Eunjeong Ma - 2014 - Science, Technology, and Human Values 39 (5):639-665.
    This article presents a case study of a recent controversy over the use of computed tomography as a diagnostic technology in South Korean hospitals. The controversy occurred in the wake of a series of conflicts in the late twentieth century over the legitimate placement of healing practices, medicinal substances, and medical technologies within Korea’s separate “Western Medicine” and “Korean Medicine” systems of health care and pharmaceutical distribution. The controversy concerned an attempt to use hi-tech imaging technology—the epitome of (...)
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  49.  7
    A Bayesian Multiresolution Approach for Noise Removal in Medical Magnetic Resonance Images.Sima Sahu, Harsh Vikram Singh, Basant Kumar & Amit Kumar Singh - 2019 - Journal of Intelligent Systems 29 (1):189-201.
    A Bayesian approach using wavelet coefficient modeling is proposed for de-noising additive white Gaussian noise in medical magnetic resonance imaging. In a parallel acquisition process, the magnetic resonance image is affected by white Gaussian noise, which is additive in nature. A normal inverse Gaussian probability distribution function is taken for modeling the wavelet coefficients. A Bayesian approach is implemented for filtering the noisy wavelet coefficients. The maximum likelihood estimator and median absolute deviation estimator are used to find the (...)
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  50.  9
    Medical Humanities: An Introduction.Thomas R. Cole, Nathan S. Carlin & Ronald A. Carson - 2014 - Cambridge University Press.
    This textbook brings the humanities to students in order to evoke the humanity of students. It helps to form individuals who take charge of their own minds, who are free from narrow and unreflective forms of thought, and who act compassionately in their public and professional worlds. Using concepts and methods of the humanities, the book addresses undergraduate and premed students, medical students, and students in other health professions, as well as physicians and other healthcare practitioners. It encourages them (...)
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