Analysis of Detecting White Blood Cells by Computer Vision Methods

Various concentrated works have been done in the area of computational vision regarding the circle and texture detections. Detection of circles in images can be beneficial for PCB components industries for the detection of capacitors in printed circuit boards, also for medicine in the detection of red cells, white blood cells, and leukocytes, and for applications which requires precision and assignments regarding the detection of circles in a digital image. In this work is utilized a benchmarking of images to detection circle boards of different radio values for the comparison with the work [1] of this article. The benchmarking of images is composed of five main images that are tested in the algorithm of detection of circles in MATLAB with different values of radio for each image. The results appoint an enhancement of 300 % concerning the algorithm proposed in work [1] showed in this article. In this work also would be plotted graphs concerning the accuracy of the new proposed algorithm with relation to the algorithm proposed in work [1], indicating better results concerning the GUI interfaces and capacity of detection circles. Keywords: computer vision, pattern recognition, an algorithm of detection, circle detection, parameter identification.

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An Improved Computer Vision Method for White Blood Cells Detection

Computational and Mathematical Methods in Medicine ◽

10.1155/2013/137392 ◽

2013 ◽

Vol 2013 ◽

pp. 1-14 ◽

Cited By ~ 10

Author(s):

Erik Cuevas ◽

Margarita Díaz ◽

Miguel Manzanares ◽

Daniel Zaldivar ◽

Marco Perez-Cisneros

Keyword(s):

Computer Vision ◽

Blood Cells ◽

Optimization Problem ◽

White Blood Cells ◽

Automatic Detection ◽

Detection Problem ◽

Image Guided ◽

De Algorithm ◽

Complete Process ◽

Unsolved Issue

The automatic detection of white blood cells (WBCs) still remains as an unsolved issue in medical imaging. The analysis of WBC images has engaged researchers from fields of medicine and computer vision alike. Since WBC can be approximated by an ellipsoid form, an ellipse detector algorithm may be successfully applied in order to recognize such elements. This paper presents an algorithm for the automatic detection of WBC embedded in complicated and cluttered smear images that considers the complete process as a multiellipse detection problem. The approach, which is based on the differential evolution (DE) algorithm, transforms the detection task into an optimization problem whose individuals represent candidate ellipses. An objective function evaluates if such candidate ellipses are actually present in the edge map of the smear image. Guided by the values of such function, the set of encoded candidate ellipses (individuals) are evolved using the DE algorithm so that they can fit into the WBCs which are enclosed within the edge map of the smear image. Experimental results from white blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique in terms of its accuracy and robustness.

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Mobile-Aware Deep Learning Algorithms for Malaria Parasites and White Blood Cells Localization in Thick Blood Smears

Algorithms ◽

10.3390/a14010017 ◽

2021 ◽

Vol 14 (1) ◽

pp. 17

Author(s):

Rose Nakasi ◽

Ernest Mwebaze ◽

Aminah Zawedde

Keyword(s):

Computer Vision ◽

Deep Learning ◽

Blood Cells ◽

Data Augmentation ◽

Expert Knowledge ◽

White Blood Cells ◽

Single Shot ◽

Good Precision ◽

Malaria Parasites ◽

Malaria Parasitemia

Effective determination of malaria parasitemia is paramount in aiding clinicians to accurately estimate the severity of malaria and guide the response for quality treatment. Microscopy by thick smear blood films is the conventional method for malaria parasitemia determination. Despite its edge over other existing methods of malaria parasitemia determination, it has been critiqued for being laborious, time consuming and equally requires expert knowledge for an efficient manual quantification of the parasitemia. This pauses a big challenge to most low developing countries as they are not only highly endemic but equally low resourced in terms of technical personnel in medical laboratories This study presents an end-to-end deep learning approach to automate the localization and count of P.falciparum parasites and White Blood Cells (WBCs) for effective parasitemia determination. The method involved building computer vision models on a dataset of annotated thick blood smear images. These computer vision models were built based on pre-trained deep learning models including Faster Regional Convolutional Neural Network (Faster R-CNN) and Single Shot Multibox Detector (SSD) models that help process the obtained digital images. To improve model performance due to a limited dataset, data augmentation was applied. Results from the evaluation of our approach showed that it reliably detected and returned a count of parasites and WBCs with good precision and recall. A strong correlation was observed between our model-generated counts and the manual counts done by microscopy experts (posting a spear man correlation of ρ = 0.998 for parasites and ρ = 0.987 for WBCs). Additionally, our proposed SSD model was quantized and deployed on a mobile smartphone-based inference app to detect malaria parasites and WBCs in situ. Our proposed method can be applied to support malaria diagnostics in settings with few trained Microscopy Experts yet constrained with large volume of patients to diagnose.

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Ultrastructural changes in murine lymphoma cells exposed to ultraviolet-A radiation

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010008482x ◽

1991 ◽

Vol 49 ◽

pp. 104-105

Author(s):

Delma P. Thomas ◽

Dianne E. Godar

Keyword(s):

Medical Devices ◽

Blood Cells ◽

White Blood Cells ◽

Consumer Products ◽

Ultrastructural Changes ◽

Ultraviolet A ◽

Uv Spectrum ◽

Lymphoma Cells ◽

Murine Lymphoma ◽

Transmission Electron

Ultraviolet radiation (UVR) from all three waveband regions of the UV spectrum, UVA (320-400 nm), UVB (290-320 nm), and UVC (200-290 nm), can be emitted by some medical devices and consumer products. Sunlamps can expose the blood to a considerable amount of UVR, particularly UVA and/or UVB. The percent transmission of each waveband through the epidermis to the dermis, which contains blood, increases in the order of increasing wavelength: UVC (10%) < UVB (20%) < UVA (30%). To investigate the effects of UVR on white blood cells, we chose transmission electron microscopy to examine the ultrastructure changes in L5178Y-R murine lymphoma cells.

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The Effect of Red Blood Cells on the ADP-induced Aggregation of Human Platelets in Flow Through Tubes

Thrombosis and Haemostasis ◽

10.1055/s-0038-1645696 ◽

1990 ◽

Vol 63 (01) ◽

pp. 112-121 ◽

Cited By ~ 18

Author(s):

David N Bell ◽

Samira Spain ◽

Harry L Goldsmith

Keyword(s):

Platelet Aggregation ◽

Shear Rate ◽

Red Blood Cells ◽

Blood Cells ◽

Platelet Rich Plasma ◽

Mean Transit Time ◽

White Blood Cells ◽

Aggregate Size ◽

Human Platelets ◽

Induced Aggregation

SummaryThe effect of red blood cells, rbc, and shear rate on the ADPinduced aggregation of platelets in whole blood, WB, flowing through polyethylene tubing was studied using a previously described technique (1). Effluent WB was collected into 0.5% glutaraldehyde and the red blood cells removed by centrifugation through Percoll. At 23°C the rate of single platelet aggregtion was upt to 9× greater in WB than previously found in platelet-rich plasma (2) at mean tube shear rates Ḡ = 41.9,335, and 1,920 s−1, and at both 0.2 and 1.0 µM ADP. At 0.2 pM ADP, the rate of aggregation was greatest at Ḡ = 41.9 s−1 over the first 1.7 s mean transit time through the flow tube, t, but decreased steadily with time. At Ḡ ≥335 s−1 the rate of aggregation increased between t = 1.7 and 8.6 s; however, aggregate size decreased with increasing shear rate. At 1.0 µM ADP, the initial rate of single platelet aggregation was still highest at Ḡ = 41.9 s1 where large aggregates up to several millimeters in diameter containing rbc formed by t = 43 s. At this ADP concentration, aggregate size was still limited at Ḡ ≥335 s−1 but the rate of single platelet aggregation was markedly greater than at 0.2 pM ADP. By t = 43 s, no single platelets remained and rbc were not incorporated into aggregates. Although aggregate size increased slowly, large aggregates eventually formed. White blood cells were not significantly incorporated into aggregates at any shear rate or ADP concentration. Since the present technique did not induce platelet thromboxane A2 formation or cause cell lysis, these experiments provide evidence for a purely mechanical effect of rbc in augmenting platelet aggregation in WB.

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White blood cells levels and PCOS: direct and indirect relationship with insulin resistance, but not with hyperandogenemia

Endocrine Abstracts ◽

10.1530/endoabs.32.p579 ◽

2013 ◽

Author(s):

Olga Papalou ◽

Sarantis Livadas ◽

Athanasios Karachalios ◽

Nektarios Benetatos ◽

George Boutzios ◽

...

Keyword(s):

Insulin Resistance ◽

Blood Cells ◽

White Blood Cells ◽

Indirect Relationship

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Endogenous Heparinoids Detected by anti-Xa Activity are Present in Blood during Acute Variceal Bleeding in Cirrhosis. A Prospective Study

Journal of Gastrointestinal and Liver Diseases ◽

10.15403/jgld.2014.1121.232.cht1 ◽

2014 ◽

Vol 23 (2) ◽

pp. 187-194 ◽

Cited By ~ 4

Author(s):

Christos Triantos ◽

Emmanuel Louvros ◽

Maria Kalafateli ◽

Anne Riddell ◽

Ulrich Thalheimer ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Variceal Bleeding ◽

Blood Cells ◽

Venous Pressure ◽

White Blood Cells ◽

International Normalized Ratio ◽

Ulcer Bleeding ◽

Factor X ◽

Packed Red Blood Cells ◽

Bacterial Peritonitis

Background & Aims: Endogenous heparinoids have been detected by thromboelastography and quantified by clotting based anti-Xa activity assays in patients with cirrhosis, but their presence in variceal bleeding has not been established yet.Methods: Clotting based anti-Xa activity was measured in A) 30 cirrhotics with variceal bleeding, B) 15 noncirrhotics with peptic ulcer bleeding, C) 10 cirrhotics without infection or bleeding, and D) 10 cirrhotics with hepatocellular carcinoma (HCC).Results: Anti-Xa activity was not detected in ulcer bleeders or in cirrhotics without infection or bleedingbut was present in seven (23%) variceal bleeders (median levels: 0.03 u/mL (0.01-0.07)) and was quantifiable for 3 days in six of seven patients. Four of seven variceal bleeders with anti-Xa activity present had HCC (p=0.023). Age, creatinine, platelet count and total infections the second day from admission were significantly correlated with the presence of measureable anti-Xa levels (p=0.014, 0.032, 0.004 and 0.019, respectively). In the HCC group, anti-Xa activity was present in three patients (30%) [median levels: 0.05 u/mL (0.01-0.06)].Conclusions: In this study, variceal bleeders and 30% of the patients with HCC had endogenous heparinoids that were detected by a clotting based anti-Xa activity assay, whereas there was no anti Xa activity present in patients with cirrhosis without infection, or bleeding or HCC, nor in those with ulcer bleeding. Thus, the anti-Xa activity is likely to be a response to bacterial infection and/or presence of HCC in cirrhosis.List of abbreviations: AFP, alpha-fetoprotein; aPTT, activated partial thromboplastin time; CP, Child-Pugh; FXa, activated factor X; GAGS, glycosaminoglycans; Hb, hemoglobin; HCC, hepatocellular carcinoma; HVPG, hepatic venous pressure gradient; INR, International normalized ratio; LMWHs, low molecular weight heparins; MELD, Model for End-stage Liver Disease; PPP, platelet-poor plasma; PRBC, packed red blood cells; PT, prothrombin time; SBP, sponataneous bacterial peritonitis; TEG, thromboelastography; WBC, white blood cells.

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