Epistemological Approach to the “Visual Perception” Concept Applied to Medicine

Abdullah Emre Taçyıldız¹*, Melih Üçer²

¹Department of Neurosurgery, Karabük University Faculty of Medicine, Karabük, Turkey

²Department of Neurosurgery, Biruni University Faculty of Medicine, Istanbul, Turkey

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Abstract

Objective: This study aims to analyze the limitations of human visual perception, compare them with the visual adaptations of other species, and explore how technological advancements—such as artificial intelligence, medical imaging, and augmented reality—have improved medical diagnostics and surgical precision.

Methods: A structured literature review was conducted, incorporating comparative analyses of visual perception across species, including frogs, dragonflies, and humans. The study evaluated the role of advanced imaging technologies, artificial intelligence-based diagnostics, and digital image processing tools in overcoming the limitations of biological vision. Selection criteria for species comparisons were based on functional adaptations and their relevance to medical imaging applications.

Results: Findings indicate that species-specific visual adaptations are optimized for survival rather than accuracy. Human vision, while advanced, is inherently constrained by physiological and neurological limitations. However, medical imaging technologies, including fluorescence-guided surgery, histology, and AI-assisted diagnostics, have significantly enhanced the precision of visual interpretation in clinical settings. The integration of computational tools, such as Adobe Photoshop for forensic and radiological analysis, further refines image accuracy and medical decision-making.

Conclusion: The interplay between biological vision and technological advancements underscores the necessity of integrating artificial intelligence and advanced imaging in medical practice. Future research should focus on optimizing these technologies to further enhance diagnostic accuracy, surgical precision, and clinical outcomes, ultimately pushing the boundaries of human visual perception.

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Introductıon

Visual perception is the process by which organisms interpret visual stimuli, combining sensory input with cognitive processing. While integral to human cognition, it is not exclusive to humans; different species have evolved distinct visual systems. Epistemologically, this concept requires distinguishing 'vision' (light reception), 'perception' (sensory interpretation), and 'visual perception' (the construction of a meaningful visual representation). This study examines visual perception from biological, cognitive, and technological perspectives^1-3. However, the accuracy and reliability of this process remain subject to evolutionary constraints and physiological limitations. While the human visual system is highly sophisticated⁴, it is not an infallible mechanism for perceiving reality; rather, it is an adaptive construct influenced by biological, environmental, and technological factors^4,5. To fully grasp the nature of human vision, it is essential to compare it with other biological visual systems. By analyzing how different species perceive and process visual information, we can uncover the adaptive trade-offs that have shaped visual cognition across evolutionary history.

This review explores the epistemological foundations of visual perception and its implications in medicine, emphasizing the inherent limitations of biological vision and the transformative role of emerging imaging technologies. By comparing visual systems across species—from primitive organisms like frogs and dragonflies to the complexity of the human eye—this study highlights the evolutionary trade-offs that define perception^6-8. While biological vision systems have evolved to maximize survival in specific ecological niches, they remain constrained by physiological and anatomical limitations. Modern medical imaging technologies, however, have progressively transcended these biological constraints, offering clinicians an enhanced ability to visualize structures beyond the scope of natural vision. Furthermore, it examines how advancements in microscopy, artificial intelligence, virtual reality, and image processing software have expanded the boundaries of medical imaging, improving diagnostic precision and surgical outcomes. Medicine takes center stage with new and demanding challenges, necessitating the evolution of human visual perception—and technology made it possible.

It can be theorized that a comprehensive understanding of the mechanisms and constraints of visual perception is essential for optimizing medical applications that depend on accurate image interpretation. By integrating insights from neuroscience, cognitive science, and technological innovation, this review aims to shed light on the evolving relationship between perception, medical imaging, and clinical decision-making.

Methods

A literature review was conducted to evaluate both historical and contemporary studies on visual perception, with a particular focus on comparative analyses of biological vision systems and their implications for medical and scientific imaging. Evolutionary perspectives and technological advancements—including microscopy, virtual and augmented reality, and artificial intelligence—were examined in terms of how they contribute to visual interpretation. This study adopts a qualitative literature review approach to investigate the evolutionary development of visual perception and its relevance to medical and scientific imaging. A comprehensive search was performed using peer-reviewed articles, books, and historical texts, emphasizing the visual systems of various species, including frogs, dragonflies, and humans. The review integrates insights from neuroscience, evolutionary biology, cognitive science, and medical imaging. Special attention was given to technological innovations, such as microscopy, virtual and augmented reality, and artificial intelligence, that enhance visualization and interpretation. By critically analyzing these sources, this study aims to elucidate the strengths and limitations of human visual perception and explore how emerging technologies help overcome its constraints.

Figure 1: Representation of the visual perception process in humans. The rightmost apple represents the actual physical object that exists in reality, reflecting light towards the observer. The middle apple illustrates the light that reaches the retina, where photoreceptor cells detect and process the incoming information. The leftmost apple represents the final visual perception formed by the brain after neural processing. This transformation highlights how perception is not a direct reproduction of reality but rather a neural reconstruction. Below, the visible light spectrum is depicted, showing the range of wavelengths the human eye can detect, with its place in the broader electromagnetic spectrum highlighted.

Dıscussıon

Evolutionary Development of Visual Systems Across Species

Epistemologically, the nature of vision, the legitimacy of visual perception, and the validity of its conveyed information should be critically assessed¹. In 1959, Lettvin et al. published a seminal article titled What the Frog's Eye Tells the Frog's Brain². Sunlight has played a crucial role as a selective force, shaping the evolution of cellular and molecular processes³. Frogs primarily rely on vision for hunting and avoiding predators, yet they lack a fovea and a dual visual system, which limits their ability to perceive stationary objects². Instead, their visual perception is motion-based, allowing them to detect only moving prey, such as worms and insects². As Darwin predicted, the evolutionary transition from a simple, imperfect eye to a complex, highly developed one—though still limited—confers advantages to its bearer³.

Dragonflies lay their eggs in water, and their visual systems have evolved to guide them to suitable water bodies for oviposition⁵. However, they do not perceive water in its entirety; instead, they detect the slight polarization of light reflected from its surface^5,6. Following the Industrial Revolution, the introduction of petroleum and asphalt roads created surfaces that polarize light more strongly than water. Consequently, dragonflies often mistake these surfaces for water and lay their eggs on them⁵. These examples illustrate how biological vision systems have evolved to meet species-specific needs, often prioritizing survival over high-resolution accuracy. In contrast, the human visual system, while still constrained by evolutionary trade-offs, has developed a more complex neural architecture to process a greater volume of visual information. Similarly, organisms that improve their survival through camouflage exploit the limitations and flaws in the visual perceptions of other species. These examples collectively suggest that visual perception is not an absolute representation of reality, but rather an adaptive mechanism shaped by ecological pressures. While these adaptations serve species-specific survival needs, the human visual system has evolved to integrate and process a much broader spectrum of visual information, enabling higher cognitive functions and complex decision-making⁵. Koch et al. also investigated the amount of information the eye transmits to the brain⁴. Their findings estimated that the human retina can transmit data at a speed roughly equivalent to that of an Ethernet connection⁴.

Biological Constraints and Perceptual Biases in Human Vision: Implications for Visual Processing

From an engineering perspective, the human eye is not optimally designed, as light must traverse multiple tissue layers before reaching the photosensitive cells⁷. The irregular arrangement of retinal cells and the presence of a blind spot compromise visual acuity. However, vision extends beyond passive light perception; it involves the active interpretation and integration of environmental data. While perception refers to the initial detection of visual stimuli, interpretation involves higher-level cognitive processing that assigns meaning to the visual input. Perception is not merely seeing but a continuous process of questioning and processing⁷. Despite these biological imperfections, the human visual system compensates through neural processing, contextual learning, and pattern recognition. The brain continuously refines raw sensory input, filling in gaps and interpreting ambiguous stimuli based on prior knowledge and expectations. This cognitive processing, while enhancing perception, also introduces biases shaped by both biological constraints and environmental influences. O'Regan argues that vision is an illusion, emphasizing that it is an active process of exploration and inquiry rather than mere passive observation, which refers to the simple reception of visual stimuli without active engagement⁷. The authors of this paper align with O'Regan's views.

The Influence of Cultural and Ecological Factors on Visual Perception

Visual perception, interpretation, and the cognitive or behavioral responses to visual stimuli are also shaped by cultural and ecological factors specific to the environments in which we live⁸. Sense-data are mental constructs formed through sensory perceptions, linking external physical objects to their representation in the mind, a concept explored by thinkers like Helmholtz, James, and Russell⁹. Hatfield argues that phenomenal experiences, such as pain and vision, should be seen as natural extensions of the physical world rather than contradictions to it⁹. The visual properties of objects in the environment—such as brightness, color, shape, distance, depth, and motion—do not definitively represent reality¹⁰. Purves et al. highlight significant discrepancies between perceived properties and the physical or mathematical realities of objects¹⁰. For instance, perceptions of brightness and darkness may contradict actual light intensity, color perceptions may differ from spectral power distributions, and size, distance, and depth perceptions often deviate from geometric and mathematical measurements¹⁰. Similarly, perceived speeds and directions of motion may not align with measured vectors. These pervasive inconsistencies between perception and reality are profound and can lead to potentially dangerous consequences¹⁰. The reliability of traditional vision concepts, based on the eye, retina, and photoreceptors, has diminished¹⁰. There is a pressing need for further research to better understand visual perception, the functions of visual circuits, and the origins of visually guided behaviors¹⁰. As a result, the information we acquire through our sensory organs is inherently uncertain¹⁰. According to Neo-Darwinian theory, the purpose of perceptual phenomena is not to depict the physical world with absolute accuracy but to foster behaviors that enhance survival and reproduction. Purves at all. contend that we do not perceive the world as it truly is, nor can we interpret it in its actual form¹⁰.

Visual representations are employed differently across disciplines, with fields such as biology, criminology, criminal justice, gerontology, information science, medicine, psychology, and sociology extensively using graphs, tables, and non-graphical illustrations¹¹. Among these, biology journals demonstrate the highest frequency of such usage¹¹. Illustrations and modern scientific visuals serve purposes such as description, classification, organization, and analysis, enhancing understanding and facilitating learning^11,12. Studies in disciplines like biology, medicine, and psychology statistically include more graphs and illustrations compared to other fields¹¹. Well-designed visuals improve the clarity and persuasiveness of research findings, simplify complex information, and, over time, support disciplinary coding and classification¹¹.

In 16th-century Europe, public cadaver dissections offered a visual spectacle of anatomy¹. With the advent of printing technologies and the press, drawn and painted images, illustrations, and graphics emerged as subjects of study¹. Anatomical drawings were compiled into atlases and textbooks, marking some of the earliest examples of visuals attaining the status of scientific data¹. The introduction of imaging techniques like X-rays uncovered aspects of the human body previously invisible to the naked eye¹. Similarly, photography sought to systematically document and present mechanical objectivity and reality¹. A significant connection exists between visual representations and the medical humanities¹. This relationship encompasses medical illustrations, the use of visual arts in clinical education, public health posters, graphic medicine, health-related videos, and the curated collections of medical museums¹³.

The Purpose of Visual Perception and the Evolutionary Process

Knill et al., adopting a Darwinian perspective, argued that perceptual predictions closer to reality confer greater adaptive advantages than inaccurate ones¹⁴. They proposed that ancestors with more accurate perceptions were more likely to survive and reproduce¹⁴. According to this view, Homo sapiens, equipped with more precise perceptual abilities, were able to produce more accurate knowledge, which significantly contributed to their evolutionary success¹⁴. As a counterargument, Mark et al. asserted that accurate perceptions do not necessarily confer an evolutionary advantage¹⁵. They argued that, under natural selection, organisms with highly accurate perceptions might even face elimination¹⁵. Hoffman similarly viewed the representation of reality through perception as overly costly⁵. He proposed that the primary role of perception is to convey utility rather than reality⁵. From an evolutionary standpoint, regardless of its intended purpose, perception remains inherently prone to error⁵.

Hoffman compares vision to a construction process, emphasizing that visual systems, equipped with 120 million photoreceptors in the retina, must construct shapes, depths, colors, motions, textures, and objects within a fraction of a second⁵. Neon color spreading serves as an example of a visual illusion, illustrating perceptual flaws in the visual system⁵.

Bridging the Gap Between Biological Vision and Technological Enhancements

The evolution of visual perception has shaped how organisms interact with their environments, influencing survival strategies and cognitive development. Understanding these biological and epistemological foundations is crucial for modern medical applications, where technological advancements—such as artificial intelligence, augmented reality, and enhanced imaging techniques—seek to compensate for human visual limitations. This section explores how bridging the gap between biological vision and technological innovations can enhance medical diagnostics, treatment precision, and overall healthcare outcomes.

Advancements in diagnostic techniques have heightened the significance of histological, anatomical, pathological, and radiological knowledge¹⁶. Accurate interpretation is critical for effectively managing this expanding body of information¹⁶. Observations such as clinical imaging, surface anatomy, skin pathologies, and radiological evaluations heavily depend on visual information¹⁶. Pereira et al. (2021) highlighted that integrating scientific research activities into medical education enhances scientific thinking, critical evaluation, and problem-solving skills¹⁷. Key competencies for physicians include enthusiasm for learning, leadership, creativity, time management, motivation, communication skills, language proficiency, and mathematical aptitude¹⁶. Zuniga et al. underscored the importance of spatial visualization, understanding laterality in others' bodies, and identifying fundamental anatomical and geometric shapes¹⁶.

Microscope       

Uluç et al. highlighted the invention of corrective lenses such as crystal magnifiers (Nimrud Lens), magnifying emeralds, reading stones, eyeglasses, telescopes, and simple microscopes to reveal unseen realities, observe finer details, and enhance perception¹⁸. Microscopes have significantly improved visual accuracy, perception, and understanding in medical applications¹⁸. For example, in surgeries like otosclerosis procedures, microscopes offer better illumination, an expanded field of view, magnification, and clarity¹⁹. In 1957, the surgical microscope was first used in a neurosurgery operating room to aid in tumor removal from a 5-year-old child¹⁸. Modern surgical microscopes now incorporate advanced features, such as blue light illumination for visualizing malignant gliomas and the ability to detect indocyanine green during intraoperative angiography¹⁸. With the integration of infrared technologies, surgical microscopes continue to evolve, enabling advanced techniques like intraoperative angiography and malignant glioma detection using systems like 'Blue 400”¹⁸. Uluç et al. predict that futuremicroscopes will be capable of simultaneously displaying MR images, angiograms, and CT scans, processing this information in real time to further enhance surgical precision and outcomes¹⁸.

Virtual Reality and Augmented Reality

"Both virtual reality (VR) and augmented reality (AR) aim to transform visual and auditory perception²⁰. In medicine, these technologies are extensively utilized in surgical training, with claims suggesting their potential to reduce surgical errors and related complications^20,21.

Virtual reality facilitates patient progress monitoring, disease prognosis, and data collection²². VR simulators have proven effective in enhancing laparoscopic skills among trainees²³. Additionally, VR offers significant benefits in surgical planning and visual guidance, positioning it as a promising tool for future medical advancements²⁰. Bluemel et al. proposed that 3D technologies, such as VR and AR, could enhance radiology-guided surgeries²⁴. For example, by projecting a virtually modeled tumor onto a tablet, they improved navigation and access to the tumor during surgery²⁵. Virtual reality and augmented reality have revolutionized visualization and data integration in the medical field, paving the way for more precise and efficient healthcare solutions²⁶.

Image Editing Software in Medical Applications

In forensic medicine, computer-assisted bite analysis utilizing Adobe Photoshop has been employed to achieve accurate and cost-effective outcomes²⁷. In radiotherapy, Adobe Photoshop has been utilized to improve the accuracy of geometric verification²⁸. The human eye often struggles to detect and interpret subtle changes in radiographic density²⁹. Photoshop software offers high accuracy and serves as an alternative measurement method for densitometric analyses²⁹. Bruises associated with child abuse are frequently observed in children; however, standardized methods for assessing their size and severity are lacking³⁰. Software tools like ImageJ and Photoshop enable consistent and reliable measurements of these injuries³⁰. The Histone Deacetylase-7-derived 7-amino acid peptide has been reported to promote wound healing through multiple mechanisms³¹. In this study, Adobe Photoshop was used to process, measure, and evaluate various images for analysis³¹. In another study, individuals with normal-weight obesity (NWO) were compared to those with normal weight and non-obesity (NWNO)³². The comparison included muscle strength, muscle thickness assessed via ultrasound, insulin resistance, and echo intensity³². Adobe Photoshop was utilized to measure echo intensity³². In forensic sciences, age progression can be achieved either artistically or through computer-assisted methods, playing a critical role in predicting the current appearance of missing persons³³. Adobe© Photoshop enables in-depth analyses in this process, while both Photoshop and emerging artificial intelligence technologies hold significant potential for advancing age progression techniques³³. The anatomical structure of the left renal vein is an important consideration in kidney donor selection³⁴. Rare variations, such as fenestrations, may require adjustments in surgical techniques³⁴. In a cadaver study, Yılmaz et al. utilized Photoshop (Adobe Inc., v24.3) to perform photogrammetric measurements of left renal vein fenestrations³⁴. Photoshop has been employed to enhance the detection and classification of pars defects in magnetic resonance images³⁵. It has also been used to visualize association fibers in the brain and to accurately delineate their boundaries³⁶.

Artificial Intelligence in Medicine

Artificial intelligence (AI) has made significant strides in medicine, including the prediction of over 5,000 protein complexes, which has facilitated the identification of new therapeutic targets^37,38. AI has demonstrated computer vision capabilities comparable to that of physicians in classifying skin cancer and has shown highly accurate results in diagnosing diabetic retinopathy^39,40. AI has the potential to revolutionize key areas such as disease diagnosis, image recognition, and outcome prediction⁴¹. In breast cancer diagnosis, AI and deep learning algorithms have outperformed mammography specialists in classifying mammograms⁴². Furthermore, AI has enhanced the resolution and quality of low-quality medical images, improving diagnostic reliability⁴³. In medical imaging, AI has become a transformative tool for data generation, processing, and analysis⁴¹. It also plays a critical role in radiation oncology by optimizing treatment plans and contributing to patient recovery. AI's advancements continue to pave the way for more precise and efficient healthcare solutions⁴¹.

Fluorescent dyes in oncological neurosurgery enhance the visualization of tumor margins and brain boundaries⁴⁴. High-resolution endoscopes improve the detection of small tumor extensions, contributing to more precise resections⁴⁴. These advancements optimize surgical outcomes, particularly in procedures focused on preserving neurological function⁴⁴. Real-time 2D/3D visualization, deep learning, and high-performance computing significantly aid neurosurgeons in surgical planning for tumor resections⁴⁵. Modern GPUs enable real-time image processing, offering critical insights into the tumor and surrounding high-risk structures⁴⁵. Boaro et al. emphasize that advancements in visualization and navigation technologies have revolutionized neurosurgery⁴⁶. Enhanced visualization and navigation have driven the development of more precise surgical instruments⁴⁶. Augmented reality (AR) is most frequently applied in neurosurgery, accounting for 71.6% of its use. AR applications are primarily utilized in neuro-oncology (36.2%) and microscope-based procedures (29.2%), contributing to safer surgeries and potential cost reductions⁴⁶. Kotwal et al. reported that hyperspectral imaging (HSI) enables surgeons to accurately differentiate pathological tissue from healthy tissue⁴⁷. Efforts to enhance visualization have extended beyond tumors⁴⁸. Virtual angioscopy has been employed in vascular surgeries, while endoluminal visualization of fistulas has directly contributed to surgical planning, leading to improved outcomes⁴⁸. MRI prototypes are also utilized as complementary tools in neurosurgical training⁴⁹.

As physicians, we recognize the inherent limitations of visual perception and the imperfections in interpreting observed realities. The challenge lies not only in accurate perception but also in applying this understanding to enhance patient care. Traditional visual perception, while fundamental to medical diagnostics, is inherently constrained by physiological and cognitive limitations. Physicians rely on subjective interpretation, which introduces variability and potential errors in decision-making. To overcome these challenges, computational imaging technologies and advanced software solutions have been developed to enhance objectivity, precision, and reproducibility in clinical assessments. Advances in optical and imaging technologies—from microscopes and medical imaging to artificial intelligence—have continuously expanded our ability to detect the unseen and refine diagnoses. Future research should focus on optimizing these technologies to further improve diagnostic precision, clinical decision-making, and the safety and efficacy of medical interventions.

Conclusion

The study underscores the inherent limitations of human visual perception and the remarkable role of technological advancements in overcoming these constraints. While biological vision has evolved for species-specific survival rather than absolute accuracy, innovations in medical imaging, artificial intelligence, and digital visualization have significantly enhanced diagnostic precision and surgical decision-making. The integration of computational tools, such as AI-assisted diagnostics and image-processing software, bridges the gap between human perception and objective medical analysis, minimizing errors and improving patient outcomes.

Furthermore, the interplay between cognitive neuroscience, evolutionary biology, and digital imaging highlights the necessity of refining existing technologies to align with the complexities of human vision. Future research should focus on enhancing the synergy between machine-based analysis and perceptual cognition, ensuring that medical imaging systems are optimized for both accuracy and clinical applicability. As computational imaging continues to evolve, its integration into routine medical practice will not only refine diagnostic capabilities but also push the boundaries of human perception, redefining the standards of modern medicine.

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