scholarly journals Blood Cell Count Using Deep Learning Semantic Segmentation

2019 ◽  
Author(s):  
Thanh Tran ◽  
Lam Binh Minh ◽  
Suk-Hwan Lee ◽  
Ki-Ryong Kwon
Keyword(s):  
Deep Learning ◽  
Blood Cell ◽  
Cell Count ◽  
Blood Cells ◽  
Blood Smear ◽  
White Blood Cells ◽  
Semantic Segmentation ◽  
Peripheral Blood Smear ◽  
Cell Counting ◽  
Blood Cell Count

Clinically, knowing the number of red blood cells (RBCs) and white blood cells (WBCs) helps doctors to make the better decision on accurate diagnosis of numerous diseases. The manual cell counting is a very time-consuming and expensive process, and it depends on the experience of specialists. Therefore, a completely automatic method supporting cell counting is a viable solution for clinical laboratories. This paper proposes a novel blood cell counting procedure to address this challenge. The proposed method adopts SegNet - a deep learning semantic segmentation to simultaneously segment RBCs and WBCs. The global accuracy of the segmentation of WBCs, RBCs, and the background of peripheral blood smear images obtains 89% when segment WBCs and RBCs from the background of blood smear images. Moreover, an effective solution to separate grouped or overlapping cells and cell count is presented using Euclidean distance transform, local maxima, and connected component labeling. The counting result of the proposed procedure achieves an accuracy of 93.3% for red blood cell count using dataset 1 and 97.38% for white blood cell count using dataset 2.

scholarly journals Deep Learning Model for the Automatic Classification of White Blood Cells

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Sarang Sharma ◽  
Sheifali Gupta ◽  
Deepali Gupta ◽  
Sapna Juneja ◽  
Punit Gupta ◽  
...  
Keyword(s):  
Deep Learning ◽  
Blood Cell ◽  
Cell Count ◽  
Blood Cells ◽  
White Blood Cells ◽  
Batch Size ◽  
Blood Cell Count ◽  
Sophisticated Equipment ◽  
Different Types ◽  
Batch Sizes

Blood cell count is highly useful in identifying the occurrence of a particular disease or ailment. To successfully measure the blood cell count, sophisticated equipment that makes use of invasive methods to acquire the blood cell slides or images is utilized. These blood cell images are subjected to various data analyzing techniques that count and classify the different types of blood cells. Nowadays, deep learning-based methods are in practice to analyze the data. These methods are less time-consuming and require less sophisticated equipment. This paper implements a deep learning (D.L) model that uses the DenseNet121 model to classify the different types of white blood cells (WBC). The DenseNet121 model is optimized with the preprocessing techniques of normalization and data augmentation. This model yielded an accuracy of 98.84%, a precision of 99.33%, a sensitivity of 98.85%, and a specificity of 99.61%. The proposed model is simulated with four batch sizes (BS) along with the Adam optimizer and 10 epochs. It is concluded from the results that the DenseNet121 model has outperformed with batch size 8 as compared to other batch sizes. The dataset has been taken from the Kaggle having 12,444 images with the images of 3120 eosinophils, 3103 lymphocytes, 3098 monocytes, and 3123 neutrophils. With such results, these models could be utilized for developing clinically useful solutions that are able to detect WBC in blood cell images.

scholarly journals White Blood Cells and Severe COVID-19: A Mendelian Randomization Study

2021 ◽  
Vol 11 (3) ◽  
pp. 195
Author(s):  
Yitang Sun ◽  
Jingqi Zhou ◽  
Kaixiong Ye
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
White Blood Cell Count ◽  
White Blood Cell ◽  
Blood Cells ◽  
Mendelian Randomization ◽  
Association Studies ◽  
White Blood Cells ◽  
Genome Wide Association Studies ◽  
Blood Cell Count

Increasing evidence shows that white blood cells are associated with the risk of coronavirus disease 2019 (COVID-19), but the direction and causality of this association are not clear. To evaluate the causal associations between various white blood cell traits and the COVID-19 susceptibility and severity, we conducted two-sample bidirectional Mendelian Randomization (MR) analyses with summary statistics from the largest and most recent genome-wide association studies. Our MR results indicated causal protective effects of higher basophil count, basophil percentage of white blood cells, and myeloid white blood cell count on severe COVID-19, with odds ratios (OR) per standard deviation increment of 0.75 (95% CI: 0.60–0.95), 0.70 (95% CI: 0.54–0.92), and 0.85 (95% CI: 0.73–0.98), respectively. Neither COVID-19 severity nor susceptibility was associated with white blood cell traits in our reverse MR results. Genetically predicted high basophil count, basophil percentage of white blood cells, and myeloid white blood cell count are associated with a lower risk of developing severe COVID-19. Individuals with a lower genetic capacity for basophils are likely at risk, while enhancing the production of basophils may be an effective therapeutic strategy.

scholarly journals White blood cells and severe COVID-19: a Mendelian randomization study

2020 ◽  
Author(s):  
Yitang Sun ◽  
Jingqi Zhou ◽  
Kaixiong Ye
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
White Blood Cell Count ◽  
White Blood Cell ◽  
Blood Cells ◽  
Mendelian Randomization ◽  
White Blood Cells ◽  
Causal Effects ◽  
Blood Cell Count ◽  
Granulocyte Count

AbstractBackgroundThe pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly emerged to seriously threaten public health. We aimed to investigate whether white blood cell traits have potential causal effects on severe COVID-19 using Mendelian randomization (MR).MethodsTo evaluate the causal associations between various white blood cell traits and severe COVID-19, we conducted a two-sample MR analysis with summary statistics from recent large genome-wide association studies.ResultsOur MR results indicated potential causal associations of white blood cell count, myeloid white blood cell count, and granulocyte count with severe COVID-19, with odds ratios (OR) of 0.84 (95% CI: 0.72-0.98), 0.81 (95% CI: 0.70-0.94), and 0.84 (95% CI: 0.71-0.99), respectively. Increasing eosinophil percentage of white blood cells was associated with a higher risk of severe COVID-19 (OR: 1.22, 95% CI: 1.03-1.45).ConclusionsOur results suggest the potential causal effects of lower white blood cell count, lower myeloid white blood cell count, lower granulocyte count, and higher eosinophil percentage of white blood cells on an increased risk of severe COVID-19.

scholarly journals PSIV-27 Peripheral complete blood cell count results in pigs are impacted by gender, sow parity, and farrowing season

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 291-292
Author(s):  
Elle Rottman ◽  
Alisun N Watson ◽  
Catherine Buck ◽  
Tsungcheng Tsai ◽  
Jeffery J Chewning ◽  
...  
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
Whole Blood ◽  
Blood Cells ◽  
White Blood Cells ◽  
Mean Corpuscular Hemoglobin ◽  
Complete Blood Cell Count ◽  
Blood Cell Count ◽  
Corpuscular Hemoglobin ◽  
Cell Counts

Abstract Complete blood cell counts have been used as a diagnostic tool across many animal species including swine. To investigate the factors that cause variation in complete blood cell count results, a total of 2,284 whole blood samples were collected from 2012 to 2019 in preweaning piglets (n = 518), nursery pigs (n = 1,704), and grower pigs (n = 60). Whole blood was collected into K2EDTA blood collection tubes and assayed using an automatic hematologic analyzer within 6 hours of collection. Data were analyzed by Mixed procedure of SAS with gender, parity group, and farrowing season as fixed effects. Body weight and age of pigs served as covariances. Farrowing season was grouped into summer (born during May to October) or winter (or November to April). Pigs that were born from first, second, and third parity, and four and above parity sows were assorted into parity group 1, 2 to 3, and 4+, respectively. Barrows had a greater concentration of total white blood cells (P < 0.01), lymphocytes (P < 0.01), and neutrophils (P < 0.01) compared to gilts. Barrows had lower mean corpuscular volume (P = 0.03), mean corpuscular hemoglobin (P < 0.01), and mean corpuscular hemoglobin concentration (P = 0.02) compared to gilts. Pigs that were farrowed in the winter season had a greater concentration of white blood cells (P = 0.01), neutrophils (P = 0.01), and the percentage of neutrophils (P = 0.03), but were lower in the percentage of lymphocytes (P = 0.03) compared to pigs farrowed during summer. Pigs born to parity four and above sows obtained a greater lymphocyte count (P = 0.01), percentage of neutrophils (P = 0.02), and percentage of lymphocytes (P = 0.01). We concluded that peripheral complete blood cells count results were affected by gender, farrowing season, and sow parity.

scholarly journals Analysis of Platelet-Rich Plasma Extraction

2017 ◽  
Vol 5 (1) ◽  
pp. 232596711667527 ◽  
Author(s):  
Jane Fitzpatrick ◽  
Max K. Bulsara ◽  
Paul Robert McCrory ◽  
Martin D. Richardson ◽  
Ming Hao Zheng
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
White Blood Cell Count ◽  
White Blood Cell ◽  
Blood Cells ◽  
Platelet Rich Plasma ◽  
White Blood Cells ◽  
Clinical Use ◽  
Blood Cell Count ◽  
High Concentrations

Background: Platelet-rich plasma (PRP) has been extensively used as a treatment in tissue healing in tendinopathy, muscle injury, and osteoarthritis. However, there is variation in methods of extraction, and this produces different types of PRP. Purpose: To determine the composition of PRP obtained from 4 commercial separation kits, which would allow assessment of current classification systems used in cross-study comparisons. Study Design: Controlled laboratory study. Methods: Three normal adults each donated 181 mL of whole blood, some of which served as a control and the remainder of which was processed through 4 PRP separation kits: GPS III (Biomet Biologics), Smart-Prep2 (Harvest Terumo), Magellan (Arteriocyte Medical Systems), and ACP (Device Technologies). The resultant PRP was tested for platelet count, red blood cell count, and white blood cell count, including differential in a commercial pathology laboratory. Glucose and pH measurements were obtained from a blood gas autoanalyzer machine. Results: Three kits taking samples from the “buffy coat layer” were found to have greater concentrations of platelets (3-6 times baseline), while 1 kit taking samples from plasma was found to have platelet concentrations of only 1.5 times baseline. The same 3 kits produced an increased concentration of white blood cells (3-6 times baseline); these consisted of neutrophils, leukocytes, and monocytes. This represents high concentrations of platelets and white blood cells. A small drop in pH was thought to relate to the citrate used in the sample preparation. Interestingly, an unexpected increase in glucose concentrations, with 3 to 6 times greater than baseline levels, was found in all samples. Conclusion: This study reveals the variation of blood components, including platelets, red blood cells, leukocytes, pH, and glucose in PRP extractions. The high concentrations of cells are important, as the white blood cell count in PRP samples has frequently been ignored, being considered insignificant. The lack of standardization of PRP preparation for clinical use has contributed at least in part to the varying clinical efficacy in PRP use. Clinical Relevance: The variation of platelet and other blood component concentrations between commercial PRP kits may affect clinical treatment outcomes. There is a need for standardization of PRP for clinical use.

scholarly journals LEUKOSITOSIS BER-FLAGGING BINTANG () BERPOTENSI ADANYA INTERFERENSI ALAT ANALISIS HEMATOLOGI OTOMATIS

2018 ◽  
Vol 17 (2) ◽  
pp. 121
Author(s):  
Christine Sugiarto ◽  
Leni Lismayanti ◽  
Nadjwa Zamalek Dalimoenthe
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
White Blood Cell Count ◽  
Ammonium Salt ◽  
Peripheral Blood ◽  
Blood Smear ◽  
Leukocyte Count ◽  
Peripheral Blood Smear ◽  
Impedance Method ◽  
Blood Cell Count

Leukocytosis is a condition in which there is an increasing number of white blood cell count in the peripheral blood compared to thenormal range based on age. Several conditions can amplify leukocyte count from haematological auto analyzers, not only those whichcorrespond to the pathologic and physiologic condition, but also with other factors, such as diluent and haematological auto analyzer’smethods. The information about these factors should be evaluated to lessen errors in the patient’s diagnosis and therapy. This casereport describes a leukocytosis in a 35-day old baby boy, diagnosed as duodenal obstruction, admitted in Paediatric Surgery Department,Hasan Sadikin Hospital, Bandung. Discrepancies occurred in this patient’s leukocyte count with some different haematological autoanalyzers. The leukocyte count from the auto analyzer by impedance method and ammonium salt diluent was 129.200/mm3 which wasindicated by a star-flagged (), while from the auto analyzer with light scatter method and anhydrous sodium sulphate and sodiumchloride diluent was 9.200/mm3, from manual count by the counting chamber with Turk diluent was 14.200/mm3 and the estimationby peripheral blood smear was 7.000–10.000/mm3. False leukocytosis by auto analyzer with impedance method was caused by thelimitation of the analyzer’s method and by the erythrocyte lysine reagent (diluent) using ammonium salt. As investigated in this case,the interferences were thought as being caused by the Lyses-resistant Red Blood Cells, thus the non-lysed/lyses cells which were enlargedin size were identified as leukocytes other than erythrocytes. It can be that the white blood concluded cell count examination which isindicated by star-flagged (), or white blood cell count >100.000/mm3 must be confirmed by manual examination (counting chamberand peripheral blood smear) or by another haematological auto analyzer method that has a different and more potent diluent

Interchangeability between immature granulocytes blood cell count measured by the Sysmex XN hematological analyzer and peripheral blood smear microscopic revision

2019 ◽  
Vol 493 ◽  
pp. S392-S393
Author(s):  
B. Fernández-Cidón ◽  
I. Cachón-Suarez ◽  
A. Sancho-Cerro ◽  
C. Imperiali-Rosario ◽  
D. Dot-Bach ◽  
...  
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
Peripheral Blood ◽  
Blood Smear ◽  
Peripheral Blood Smear ◽  
Blood Cell Count

scholarly journals A case of acute leukaemia in a 38-years old female

2012 ◽  
Vol 18 (2) ◽  
pp. 83-85 ◽  
Author(s):  
Barbu Adina
Keyword(s):  
Stem Cells ◽  
Bone Marrow ◽  
Blood Cell ◽  
Microscopic Examination ◽  
Blood Cells ◽  
Acute Leukaemia ◽  
Blood Smear ◽  
White Blood Cells ◽  
Peripheral Blood Smear ◽  
Large Numbers

Abstract Leukaemia is cancer that starts in blood-forming tissues, such as bone marrow, and causes large numbers of abnormal blood cells to be produced and enter the bloodstream. The stem cells usually develop into a type of white blood cell called myeloblasts which do not mature into healthy white blood cells. The leukaemia cells are unable to do their usual work and can build up in the blood and bone marrow so there is less space for healthy white blood cells, red blood cells and platelets. Anemia is a major sign but diagnosis is provided only microscopic examination of peripheral blood smear.

PENENTUAN KRITERIA PENILAIAN KESAN JUMLAH LEUKOSIT PADA PEMERIKSAAN APUSAN DARAH TEPI

2018 ◽  
Vol 3 (2) ◽  
pp. 52-61
Author(s):  
Dzikra Arwie ◽  
Islawati
Keyword(s):  
Data Analysis ◽  
Statistical Analysis ◽  
Blood Cells ◽  
Blood Smear ◽  
White Blood Cells ◽  
Peripheral Blood Smear ◽  
Field Of View ◽  
Laboratory Observation ◽  
Number Of Cells

Leukocytes or white blood cells have a characteristic characteristic of different cells. Determination of the impression of the number of leukocytes is determined in the number of cells in the field of view. While the number of viewable field cells expressed is still quite varied. The purpose of this study was to determine the number of leukocytes in the field of view and expressed the impression of a sufficient amount. This research was conducted at the Laboratory of Health Analyst Department Panrita Husada Bulukumba on 9 April 2017 to 14 July 2017. This type of research is a laboratory observation that aims to determine the criteria for assessing the impression of the number of leukocytes on a peripheral blood smear. Data analysis using statistical analysis is the average and standard deviations to determine the impression of the number of leukocytes and use 3 inspection zones. The results of this study obtained results in zone IV the number of leukocyte impressions said to be sufficient was 7-10, in zone V the number of leukocyte impressions said to be sufficient was 4-9, and in zone VI the number of leukocyte impressions said to be sufficient was 3-8.  

Sign in / Sign up

Export Citation Format

Share Document