ReviewMedical & biological engineering & computing2022
Analysis of red blood cells from peripheral blood smear images for anemia detection: a methodological review.
Review in Medical & biological engineering & computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 65 citations in OpenAlex.
- Decoding the Role of Caveolin-1 in Morphological Diversity and Self-Renewal of Breast Cancer Cells.Cell proliferation · 2026Article
- Anaemia: A Scientific Overview on Types and Recent Advancements in the Detection of Anaemia.Cardiovascular & hematological agents in medicinal chemistry · 2026Review
- Exercise-induced oxidative and hematological responses in adolescent female swimmers during the luteal phase.Frontiers in physiology · 2026Article
- Spectral-aware CNN with learnable biorthogonal units and depthwise convolutions for multi-class blood cell classification.MethodsX · 2025Article
- Clinical utility of calculated haematological parameters in the diagnosis of iron deficiency anaemia in pregnant women.Biomedical reports · 2025Article
- Recent advances in microscale techniques for red blood cells manipulation.Biomicrofluidics · 2025Review
- Assessment of anemia recovery using peripheral blood smears by deep semi-supervised learning.Annals of hematology · 2025Article
- AI-assisted diagnosis of anemia through peripheral smear image analysis: A cross-validation study.Bioinformation · 2025Article
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- Article
- Biophysical profiling of red blood cells from thin-film blood smears using deep learning.Heliyon · 2024Article
- Artificial Intelligence (AI)-Based Detection of Anaemia Using the Clinical Appearance of the Gingiva.Cureus · 2024Article
- Article
- Embedded-deep-learning-based sample-to-answer device for on-site malaria diagnosis.Frontiers in bioengineering and biotechnology · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Anemia is a blood disorder which is caused due to inadequate red blood cells and hemoglobin concentration. It occurs in all phases of life cycle but is more dominant in pregnant women and infants. According to the survey conducted by the World Health Organization (WHO) (McLean et al., Public Health Nutr 12(4):444-454, 2009), anemia affects 1.62 billion people constituting 24.8% of the population and is considered the world's second leading cause of illness. The Peripheral Blood Smear (PBS) examination plays an important role in evaluating hematological disorders. Anemia is diagnosed using PBS. Being the most powerful analytical tool, manual analysis approach is still in use even though it is tedious, prone to errors, time-consuming and requires qualified laboratorians. It is evident that there is a need for an inexpensive, automatic and robust technique to detect RBC disorders from PBS. Automation of PBS analysis is very active field of research that motivated many research groups to develop methods using image processing. In this paper, we present a review of the methods used to analyze the characteristics of RBC from PBS images using image processing techniques. We have categorized these methods into three groups based on approaches such as RBC segmentation, RBC classification and detection of anemia, and classification of anemia. The outcome of this review has been presented as a list of observations.
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