Analysis of red blood cells from peripheral blood smear images for anemia detection: a methodological review
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Title
Analysis of red blood cells from peripheral blood smear images for anemia detection: a methodological review
Authors
Keywords
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Journal
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
Volume 60, Issue 9, Pages 2445-2462
Publisher
Springer Science and Business Media LLC
Online
2022-07-15
DOI
10.1007/s11517-022-02614-z
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- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- (2017) Vijay Badrinarayanan et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Pilot Study on the Performance of a New System for Image Based Analysis of Peripheral Blood Smears on Normal Samples
- (2017) Preethi S. Chari et al. INDIAN JOURNAL OF HEMATOLOGY AND BLOOD TRANSFUSION
- Automated three-dimensional morphology-based clustering of human erythrocytes with regular shapes: stomatocytes, discocytes, and echinocytes
- (2017) Ezat Ahmadzadeh et al. JOURNAL OF BIOMEDICAL OPTICS
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- (2017) Hany A. Elsalamony MEASUREMENT
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- (2017) Vasundhara Acharya et al. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
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- (2017) Mohammed Khalaf et al. NEUROCOMPUTING
- Pilot Study on the Performance of a New System for Image Based Analysis of Peripheral Blood Smears on Normal Samples
- (2017) Preethi S. Chari et al. Indian Journal of Hematology and Blood Transfusion
- A deep convolutional neural network for classification of red blood cells in sickle cell anemia
- (2017) Mengjia Xu et al. PLoS Computational Biology
- Healthy and unhealthy red blood cell detection in human blood smears using neural networks
- (2016) Hany A. Elsalamony MICRON
- Erythrocyte shape classification using integral-geometry-based methods
- (2015) X. Gual-Arnau et al. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
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- (2015) Xudong Wei et al. Journal of Innovative Optical Health Sciences
- Red Blood Cell Cluster Separation From Digital Images for Use in Sickle Cell Disease
- (2015) Manuel Gonzalez-Hidalgo et al. IEEE Journal of Biomedical and Health Informatics
- Automatic Detection and Quantification of WBCs and RBCs Using Iterative Structured Circle Detection Algorithm
- (2014) Yazan M. Alomari et al. Computational and Mathematical Methods in Medicine
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- (2014) Howard Lee et al. PATTERN RECOGNITION LETTERS
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- (2013) Margarita Walliander et al. Diagnostic Pathology
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- (2013) J. Ford International Journal of Laboratory Hematology
- Automatic image segmentation and classification based on direction texton technique for hemolytic anemia in thin blood smears
- (2013) Hung-Ming Chen et al. MACHINE VISION AND APPLICATIONS
- Quantitative microscopy approach for shape-based erythrocytes characterization in anaemia
- (2012) D.K. DAS et al. JOURNAL OF MICROSCOPY
- Structural and textural classification of erythrocytes in anaemic cases: A scanning electron microscopic study
- (2012) Sirsendu Bhowmick et al. MICRON
- White Blood Cell Segmentation for Acute Leukemia Bone Marrow Images
- (2012) Lim Huey Nee et al. Journal of Medical Imaging and Health Informatics
- Classification of complete blood count and haemoglobin typing data by a C4.5 decision tree, a naïve Bayes classifier and a multilayer perceptron for thalassaemia screening
- (2011) Damrongrit Setsirichok et al. Biomedical Signal Processing and Control
- Image Analysis Approach for Development of a Decision Support System for Detection of Malaria Parasites in Thin Blood Smear Images
- (2011) Keerthana Prasad et al. JOURNAL OF DIGITAL IMAGING
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- (2009) Gloria Díaz et al. JOURNAL OF BIOMEDICAL INFORMATICS
- Worldwide prevalence of anaemia, WHO Vitamin and Mineral Nutrition Information System, 1993–2005
- (2008) Erin McLean et al. PUBLIC HEALTH NUTRITION
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