An Automated Method for Counting Red Blood Cells using Image Processing
TLDR
Technique has been introduced to count the RBCs automatically and images are classified on the basis of color, texture and morphology, namely elliptocytes, echinocytes, tear drop cells and macrocytes, which achieves overall accuracy of 91.667% and is computationally very efficient.About:
This article is published in Procedia Computer Science.The article was published on 2020-01-01 and is currently open access. It has received 21 citations till now. The article focuses on the topics: Elliptocytes.read more
Citations
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Journal ArticleDOI
Identification of Sickle Cell Anemia Using Deep Neural Networks
TL;DR: The proposed approach tackles the limitations of manual research by implementing a powerful and efficient MLP (Multi-Layer Perceptron) classification algorithm that distinguishes Sickle Cell Anemia (SCA) into three classes: Normal (N), Sickle Cells (S) and Thalassemia (T) in red blood cells.
Journal ArticleDOI
CNN-SSPSO: A Hybrid and Optimized CNN Approach for Peripheral Blood Cell Image Recognition and Classification
TL;DR: The model based on the CNN approach optimized by SSPSO achieves high classification accuracy and provides automatic peripheral blood cell classification and an improved version of salp swarm optimizer (SSO) using particle swarm optimization (PSO) to attain competitive classification performance over the database of the blood cell images.
Journal ArticleDOI
Automated Identification Model of Ground-Glass Opacity in CT-Scan Image by COVID-19
TL;DR: This research can be used as a model recommendation in identifying thorax damage due to COVID-19 very well in following up on more intensive treatment in the future.
Proceedings ArticleDOI
Automatic Counting Red Blood Cells in the Microscopic Images by EndPoints Method and Circular Hough Transform
TL;DR: A new method is presented for counting incomplete or cropped RBCs by Circular Hough Transform (CHT) and another method called EndPoints method which will be described in the following.
Journal ArticleDOI
An Overview on Detection, Counting and Categorization of Silkworm Eggs using Image Analysis Approach
H. Pavitra,C. G. Raghavendra +1 more
TL;DR: An overview of the various types of algorithms used to count, classify, and detect silkworm eggs, whether the silworm eggs are fertilized (hatched) or unfertilized (unhatched), using image processing approaches is provided in this article .
References
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Journal ArticleDOI
Detection and Counting of Red Blood Cells in Blood Cell Images using Hough Transform
TL;DR: This paper presents an approach to automatic segmentation and counting of red blood cells in microscopic blood cell images using Hough Transform and discusses the results achieved by the proposed method and the conventional manual counting method.
Proceedings ArticleDOI
An overview of lossless digital image compression techniques
Ming Yang,Nikolaos G. Bourbakis +1 more
TL;DR: JPG-LS and JPEG-2000 are the latest ISO/ITU standards for compressing continuous-tone images and are based on LOCO-I algorithm, which was chosen to incorporate the standard due to its good balance between complexity and efficiency.
Proceedings ArticleDOI
Automated Red Blood Cells Counting in Peripheral Blood Smear Image Using Circular Hough Transform
TL;DR: A method to count a total number of RBC in peripheral blood smear image by using circular Hough transform (CHT) method, which shows that from ten samples of peripheralBlood smear image, the accuracy using CHT method is 91.87%.
Journal ArticleDOI
Red blood cells estimation using hough transform technique
TL;DR: The aim of this research is to produce a computer vision system that can detect and estimate the number of red blood cells in the blood sample image using Morphological, a very powerful tool in image processing, and it is been used to segment and extract thered blood cells from the background and other cells.
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Red Blood Cell Cluster Separation From Digital Images for Use in Sickle Cell Disease
Manuel González-Hidalgo,Fidel Guerrero-Peña,Silena Herold-Garcia,Antoni Jaume-i-Capó,Pedro Marrero-Fernández +4 more
TL;DR: This paper proposes a method for the analysis of the shape of erythrocytes in peripheral blood smear samples of sickle cell disease, which uses ellipse adjustments and a new algorithm for detecting notable points and applies a set of constraints that allow the elimination of significant image preprocessing steps proposed in previous studies.
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