Anemia eyes
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Anemia Detection and Ocular Manifestations: Insights from Recent Research
Non-Invasive Anemia Detection Using Eye Conjunctiva
Principal Component Analysis and K-Nearest Neighbor Methods
Recent advancements in non-invasive anemia detection have focused on analyzing the conjunctiva of the eye. One study utilized Principal Component Analysis (PCA) and K-Nearest Neighbor (K-NN) methods to detect anemia by examining images of the eye's conjunctiva. This approach achieved an accuracy of 87.5% with a specific image size and parameter settings, demonstrating the potential of non-invasive techniques in anemia detection 1.
Computerized Techniques and Machine Learning
Another study developed a computerized technique to detect anemia by capturing images of the eye conjunctiva and processing them to extract the region of interest (ROI). The mean intensity values of red and green components of the image pixels were analyzed using a machine learning algorithm, achieving an impressive accuracy of 93% on 99 test subjects. This method offers a fast, cost-effective, and non-invasive alternative to traditional blood tests 2.
Image Segmentation and Thresholding
Image segmentation algorithms have also been employed to extract the palpebral conjunctiva from eye images. These segmented regions are then analyzed to estimate hemoglobin levels, indicating whether a patient is anemic. This method highlights the importance of precise image processing techniques in non-invasive anemia detection 4. Additionally, another study used image processing and thresholding to analyze the anterior conjunctival pallor of the eye, achieving an accuracy of 78.9% in detecting anemia 5.
Ocular Manifestations of Anemia
Retinal and Choroidal Thickness Variations
Anemia can lead to significant changes in the retina and choroid. A study analyzing subfoveal retinal (CRT) and choroidal (SFCT) thickness in anemic patients found that those with anemia had thicker retinas and choroids compared to healthy controls. This thickening correlated negatively with hemoglobin levels and visual acuity, indicating that anemia can impact ocular health 6.
Idiopathic Aplastic Anemia and Retinal Findings
Idiopathic aplastic anemia (AA) is a rare condition with notable ocular manifestations. A retrospective study of 719 AA patients revealed that 37% had retinal hemorrhages, and other findings included central retinal vein occlusion-like pictures, optic disc edema, cotton-wool spots, and macular edema. These findings underscore the need for comprehensive ocular examinations in patients with AA 3.
Conclusion
The detection of anemia through non-invasive methods using eye conjunctiva analysis is a promising field, with various studies demonstrating high accuracy rates using different image processing and machine learning techniques. Additionally, anemia can lead to significant ocular changes, necessitating regular eye examinations for affected individuals. These advancements in non-invasive detection and understanding of ocular manifestations can improve patient outcomes and provide accessible healthcare solutions, especially in underdeveloped regions.
Sources and full results
Most relevant research papers on this topic
Anemia Detection Through Conjunctiva on Eyes Using Principal Component Analysis Method and K-Nearest Neighbor
Anemia detection through the conjunctiva of the eye using Principal Component Analysis and K-Nearest Neighbor methods has an accuracy of 87.5%, making it a non-invasive method for detecting anemia.
A Noninvasive Computerized Technique to Detect Anemia Using Images of Eye Conjunctiva
This study developed a noninvasive technique using eye conjunctiva images, achieving an accuracy of 93% in detecting anemia without invasive blood tests.
Ocular manifestations of idiopathic aplastic anemia: retrospective study and literature review
Aplastic anemia patients may experience ocular manifestations, such as retinal hemorrhage, optic disc edema, and dry eyes, requiring multidisciplinary management.
Image Segmentation of Eye for Non-invasive Detection of Anemia
This paper presents image segmentation algorithms for extracting the palpebral conjunctiva from patient's eye images, which can be used to estimate the hemoglobin level and determine if the patient is anemic or not.
Detection of anemia from image of the anterior conjunctiva of the eye by image processing and thresholding
Our automated, non-invasive method for detecting anemia using an eye color analysis from a smartphone camera has a 78.9% accuracy, making it a viable alternative to invasive blood tests in underdeveloped areas.
Observational StudyChoroidal and retinal thickness variations in anaemia and anaemic retinopathy
Patients with anemia have a thicker retina and choroid compared to normal healthy controls.
Observational StudyIron deficiency anemia detection using machine learning models: A comparative study of fingernails, palm and conjunctiva of the eye images
Machine learning models, particularly CNN, are effective in detecting iron-deficiency anemia in children and pregnant women, with a 99.12% accuracy.
Neural network based non‐invasive method to detect anemia from images of eye conjunctiva
Our neural network model accurately detects anemia from eye conjunctiva images, providing a non-invasive method with high sensitivity and specificity.
Prevalence and associated factors of anemia in a Russian population: the Ural eye and medical study
Anemia prevalence in Russia is 23.6%, with higher hemoglobin levels associated with male gender, higher waist-hip circumference ratio, car ownership, and higher blood bilirubin and triglyceride levels.
Observational Study
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