We compare methods of aggregating repeated decisions from a single decision maker to improve medical image decision making using metacognitive processes (confidence judgments) and representational similarity from artificial neural networks for both novice and expert participants.

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 embodied skills are actualized during the moments of visual perception. My argument is that biology, society and instruments constitute unique individual ontologies influencing specialist readings of the technological output, in other words, putting limits on the ‘‘truth-to-nature’’ relation, which is so much sought for in science. (shrink)

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? How (...) are standards for interpretation to be fixed? Is there a problem of overutilization of such tests? How should uncertainty be communicated to patients? How to cope with incidental findings? This book is of interest and importance to scholars of philosophy of medicine at all levels, from undergraduates to researchers, to medical researchers and practitioners (radiologists and nuclear physicians) interested in a critical appraisal of the methodology of their discipline and in the ethical principles and consequences of their work. -/- . (shrink)

Due to advancements in technology such as data science and artificial intelligence, healthcare research has gained momentum and is generating new findings and predictions on abnormalities leading to the diagnosis of diseases or disorders in human beings. On one hand, the extensive application of data science to healthcare research is progressing faster, while on the other hand, the ethical concerns and adjoining risks and legal hurdles those data scientists may face in the future slow down the progression of healthcare research. (...) Simply put, the application of data science to ethically guided healthcare research appears to be a dream come true. Hence, in this paper, we discuss the current practices, challenges, and limitations of the data collection process during medical image analysis (MIA) conducted as part of healthcare research and propose an ethical data collection framework to guide data scientists to address the possible ethical concerns before commencing data analytics over a medical dataset. (shrink)

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 (...) the story of human reproduction. The article argues that visualisation of the gametes and the central role they play in contemporary imaginations of reproduction may offer vital contributions to the rather rapid acceptance and normalisation of assisted reproduction. (shrink)

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 (...) system to allow for the discrimination of the desired categories. It is no wonder that the visualizations referring to the body also show effects which have no physiological correlation within the body. Still such images are often used as if they were one-to-one correlates of the body. This has impacts, e.g. for their use as standardizing instances, resulting in new definitions of the normed healthy body, sickness or pathologies, maleness and femaleness and in determinisms as opposed to the brain's plasticity and variability, both in time and space, inter- as well as intra-individually. (shrink)

This volume addresses the interdependencies between visual technologies and epistemology with regard to our perception of the medical body. It explores the relationships between the imagination, the body, and concrete forms of visual representations: Ranging from the Renaissance paradigm of anatomy, to Foucault's "birth of the clinic" and the institutionalised construction of a "medical gaze"; from "visual" archives of madness, psychiatric art collections, the politicisation and economisation of the body, to the post-human in mass media representations. Contributions to (...) this volume investigate medical bodies as historical, technological, and political constructs, constituted where knowledge formation and visual cultures intersect. Contributors are: Axel Fliethmann, Michael Hau, Birgit Lang, Carolyn Lau, Heikki Lempa, Stefanie Lenk, Joanna Madloch, Barry Murnane, Jill Redner, Claudia Stein, Elizabeth Stephens, Corinna Wagner, and Christiane Weller. (shrink)

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 homomorphic filtering functions, which can attenuate the low frequencies and amplify the high frequencies. A linear adjustment is carried out on the low frequency of the highest level. Then, the wavelet reconstruction course is used to obtain the final enhanced image. Experiments on magnetic resonance images of temporomandibular joint soft tissues have shown that the proposed method can effectively eliminate the non-uniform luminance distribution of medical images. Its performance is much better than traditional Butterworth homomorphic filtering algorithm whether in subjective vision quality or objective evaluations such as detailed information entropy and average gradient. (shrink)

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 Standard (...) articles, on the smiling, walking, and waving babies that the images purport to show, was echoed throughout the worldwide media coverage that followed. In July 2004, Sir David Steel, sponsor of the 1967 Abortion Act, publicly stated that the Create images led him to believe it was time to review the legal time limit for abortions. Prime Minister Tony Blair said he considered calls for such a review reasonable.What interests me here is the powerful role that biomedical imaging, and the human artifice it involves, can play in influencing the nature, timing, and tone …. (shrink)

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: (i) embedding (...) and (ii) extraction. In this paper, we securely share three types of patient information, medical image, electronic health record (EHR), and face image from one hospital to another hospital. Initially, all the three inputs are encrypted and the information is concordant. In order to enhance the robustness of the crypto-watermarking system, the obtained bit stream is compressed, and the compressed bit streams are embedded into the cover image. The same process is repeated for the extraction process. The experimentation result is carried out using different medical images with EHR, and the effectiveness of the proposed algorithm is analyzed with the help of peak signal to noise ratio. (shrink)

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 (...) images and discerning its class based on reversion value such as partial F value. SWLDA begins with picking an equivalence comprising the sole finest X variable and then puts in effort to add more Xs individually, providing the situations are adequate. The process of adding and picking is based on F value to determine which variable would be entered. Then, the picked or the default F-to-enter value is compared with the uppermost partial F value. After this step, the forward addition or backward removal begins and whether the partial test values for all the predictor variables already in the line are estimated is known. Then, the comparison is made between the lowermost partial test value and preselected or defaulting consequence levels such as F0. Finally, the system is trained by employing support vector machine to label the blood images. The performance of the proposed approach is assessed by employing 8 different datasets of blood structures. It is assured that the proposed method has achieved significant results under different blood structure images including COVID-19. (shrink)

Artificial intelligence (AI) has attracted an increasing amount of attention, both positive and negative. Its potential applications in healthcare are indeed manifold and revolutionary, and within the realm of medical imaging and radiology (which will be the focus of this paper), significant increases in accuracy and speed, as well as significant savings in cost, stand to be gained through the adoption of this technology. Because of its novelty, a norm of keeping humans “in the loop” wherever AI mechanisms are (...) deployed has become synonymous with good ethical practice in some circles. It has been argued that keeping humans “in the loop” is important for reasons of safety, accountability, and the maintenance of institutional trust. However, as the application of machine learning for the detection of lumbar spinal stenosis (LSS) in this paper’s case study reveals, there are some scenarios where an insistence on keeping humans in the loop (or in other words, the resistance to automation) seems unwarranted and could possibly lead us to miss out on very real and important opportunities in healthcare—particularly in low-resource settings. It is important to acknowledge these opportunity costs of resisting automation in such contexts, where better options may be unavailable. Using an AI model based on convolutional neural networks developed by a team of researchers at NUH/NUS medical school in Singapore for automated detection and classification of the lumbar spinal canal, lateral recess, and neural foraminal narrowing in an MRI scan of the spine to diagnose LSS, we will aim to demonstrate that where certain criteria hold (e.g., the AI is as accurate or better than human experts, risks are low in the event of an error, the gain in wellbeing is significant, and the task being automated is not essentially or importantly human), it is both morally permissible and even desirable to kick the humans out of the loop. (shrink)

This article explores the profound impact of visualism and visual perception in the context of medical imaging diagnostics. It emphasizes the intricate interplay among vision, embodiment, subjectivity, language, and historicity within the realm of medical science and technology, with a specific focus on image consciousness. The study delves into the role of subjectivity in perception, facilitating the communication of opacity and historicity to the perceiving individual. Additionally, it scrutinizes the image interpretation process, drawing parallels to text interpretation and (...) highlighting the influence of personal biases and individuality in medical practice. By revisiting Husserl’s conceptualization of “image consciousness” and introducing the notion of “image theme”, the paper seeks to establish a theoretical framework for making sense of images within the context of technological interpretation. A key objective is to enhance the phenomenology of technology through a systematic analysis of medical imaging diagnosis, contributing to an expanded epistemological foundation for medical practice. The article recognizes that the construction of medical knowledge incorporates subjective elements, especially within a historical context. The interpretation of images involves both instrumental and expert interpretation, with human subjectivity playing a crucial role. The article asserts that human creativity and conscious engagement are indispensable in interpreting all medical images. (shrink)

Deep learning techniques, which use a massive technology known as convolutional neural networks, have shown excellent results in a variety of areas, including image processing and interpretation. However, as the depth of these networks grows, so does the demand for a large amount of labeled data required to train these networks. In particular, the medical field suffers from a lack of images because the procedure for obtaining labeled medical images in the healthcare field is difficult, expensive, (...) and requires specialized expertise to add labels to images. Moreover, the process may be prone to errors and time-consuming. Current research has revealed transfer learning as a viable solution to this problem. Transfer learning allows us to transfer knowledge gained from a previous process to improve and tackle a new problem. This study aims to conduct a comprehensive survey of recent studies that dealt with solving this problem and the most important metrics used to evaluate these methods. In addition, this study identifies problems in transfer learning techniques and highlights the problems of the medical dataset and potential problems that can be addressed in future research. According to our review, many researchers use pre-trained models on the Imagenet dataset in many applications such as skin cancer, breast cancer, and diabetic retinopathy classification tasks. These techniques require further investigation of these models, due to training them on natural, non-medical images. In addition, many researchers use data augmentation techniques to expand their dataset and avoid overfitting. However, not enough studies have shown the effect of performance with or without data augmentation. Accuracy, recall, precision, F1 score, receiver operator characteristic curve, and area under the curve were the most widely used measures in these studies. Furthermore, we identified problems in the datasets for melanoma and breast cancer and suggested corresponding solutions. (shrink)

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 recommendations of the ICMJE. Clinical image consent requirements varied widely from journal to journal. None of the studied journals, even amongst n = 4 ICMJE members or n = 8 journals who self-report adherence to ICMJE guidelines, comply with all of the recommendations of the ICMJE. Half of studied journals require a journal-specific consent form. Among top medical journals there is significant heterogeneity in consent requirements for clinical images. Variability of consent requirements is neither practical nor rational; inconsistent requirements create uncertainty for authors, present impediments to dissemination of scholarship, and undermine a shared professional understanding of how best to protect patient privacy. We propose adopting a standardized consent form and process for publication of identifiable images in medical journals, with uniform elements and explicit definitions. (shrink)

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.

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 of self-continuity and the façade of familiarity. Phenomenologically, upheaval shows itself when givenness both precedes and participates in the giving of phenomena such as medical students’ “before and after” images of psychoanalysis. They discover and reconfigure their erstwhile absolute positions and values into reconfigurations of self and prior commitments. The turning point from their instrumental use of knowledge to reconfigurations of how they situate themselves in the world decisively comes when teaching and learning become an event in se that disturbs their sense of order.Following Husserl, phenomenological psychological observation has required us to go from the events of history to a sense of history. Would, however, that we could stay at the level of events much longer to see images explode and exceed their horizons from the illusion of order, and patterned repetition disrupted by surprise, upheaval and indeterminacy in the spirit of Alain Badiou! (shrink)

Book reviewed in this article: The Physician's Covenant: Images of the Healer in Medical Ethics. By William F. May.

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 notion of (...) reliability, we argue that PET is a highly theory-laden and non-immediate knowledge procedure, in spite of the photographic-like quality of the images it delivers; the diagnostic conclusions based on the interpretation of PET images are population-dependent; PET images require interpretation, which is inherently observer-dependent and therefore variable. We conclude with a three-step methodological proposal for enhancing the reliability of advanced medical imaging. (shrink)

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 used to describe clinical images, the time spent analyzing the images, and the number of clinically relevant observations. (shrink)

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 (...) making, cannot account for the need for the other kind of evidence. Weber (Int Stud Philos Sci 23(2):277–295, 2009) has suggested to the contrary that Giere’s probabilistic analysis of causality survives this criticism. In this paper, we look in detail at the case of medical imaging technology, which, we argue, supports the thesis of Russo and Williamson, and we respond to Weber’s suggestion, arguing that Giere’s account does not survive the criticism. (shrink)

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 to extract the electronic medical record text, integrates the two features using the full connection layer network and Softmax classifier, and obtains a method that can assist the diagnosis from two modes. Experiments show that the proposed scheme on average improves 3.05% in accuracy compared to individual image or text modes, and the best performing GoogleNet + Bi-LSTM model achieves 96.61% accuracy; although slightly less in recall, it performs better on F1 values, and has provided feasible new ideas and new methods for research in the field of multi-model medical-assisted diagnosis. (shrink)

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 disease detection accuracy. The network learning process is enhanced according to the AdaDelta learning process, which replaces the learning parameter with a delta value. This process minimizes the error rate while recognizing the disease. The efficiency of the system evaluated using image retrieval in medical application dataset. This process helps to determine the various diseases such as breast, lung, and pediatric studies. (shrink)

Watermarking is one of the most common techniques used to protect data’s authenticity, integrity, and security. The obfuscation in the frequency domain used in the watermarking method makes the watermarking stronger than the obfuscation in the spatial domain. It occupies an important place in watermarking works in imperceptibility, capacity, and robustness. Finding the optimal location to hide the watermarking is one of the most challenging tasks in these methods and affects the method’s performance. In this article, sample identification information is (...) processed with the method of watermaking on the hiding environment created by using a chaos-based random number generator on biomedical data to provide solutions to problems such as visual attack, identity theft, and information confusion. In order to obtain biomedical data, a lensless digital in-line holographic microscopy setup was designed, and holographic data of human blood and cancer cell lines, which are widely used in the laboratory environment, were obtained. The standard USAF 1951 target was used to evaluate the resolution of our imaging setup. Various QR codes were generated for medical sample identification, and the captured medical data were processed by watermarking it with chaos-based random number generators. A new method using chaos-based discrete wavelet transform and singular value decomposition has been developed and applied to high-resolution data to eliminate the problem of encrypted data being directly targeted by third-party attacks. The performance of the proposed new watermarking method has been demonstrated by various robustness and invisibility tests. Experimental results showed that the proposed scheme reached an average PSNR value of 564588 dB and SSIM value of 0.9972 against several geometric and destructive attacks, which means that the proposed method does not affect the image quality and also ensures the security of the watermarking information. The results of the proposed method have shown that it can be used efficiently in various fields. (shrink)

Visual images are widely used in medical and patient education to enhance spoken or written explanations. This paper considers the role of such illustrations in shaping conceptions of the body; specifically, it addresses depictions of variant sexual anatomy and their part in the discursive production of intersex bodies. Visual language—even didactic, ‘factual’ visual language—carries latent as well as manifest content, and influences self-perceptions and social attitudes. In the case of illustrations about atypical sex development, where the need for (...) non-stigmatising communication is crucial, it is especially important to consider the implicit messages conveyed by imagery and compositional strategies. (shrink)

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, the chronology of the development of illustration in both fields (from the first illustrated incunabula to the mid-sixteenth century) is compared, and some explanations (economical, epistemological, cultural) are proposed and questioned. -/- . (shrink)

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 (...) to consider the ethical and existential issues related to the experience of disease, care of the dying, health policy, religion and health, and medical technology. Case studies, images, questions for discussion, and role-playing exercises help readers to engage in the practical, interpretive, and analytical aspects of the material, developing skills for critical thinking as well as compassionate care. (shrink)

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 modern (...) medicine—in a clinic that maintains a strong ideological attachment to Korean healing traditions. A close study of this dispute, based on interviews, participant observation, and documentary analysis, showed that discursive positions taken about the translatability of medical technologies changed with the context of dispute, and did not reflect a stable epistemic boundary between rival medical paradigms. (shrink)

The neurocentric worldview that identifies the essence of the human being with the material brain has become a central paradigm in current academic discourse. Israeli researchers also seek to understand educational principles and processes via neuroscientific models. On this background, the article uncovers the central role that visual brain images play in the learning-disabilities field in Israel. It examines the place brain images have in the professional imagination of didactic-diagnosticians as well as their influence on the diagnosticians' clinical (...) attitudes. It relies on two theoretical fields: sociology and anthropology of the body and sociology of neuromedical knowledge. The research consists of three methodologies: ethnographic observations, in-depth interviews, and rhetorical analysis of visual and verbal texts. It uncovers the various rhetorical and ideological functions of brain images in the field. It also charts the repertoire of rhetorical devices which are utilized to strengthen the neuroreducionist messages contained in the images. (shrink)