A MATLAB model for diagnosing sickle cells and other blood abnormalities using image processing

<span lang="EN-US">The conventional method for detecting blood abnormality is time consuming and lacks the high level of accuracy. In this paper a MATLAB based solution has been suggested to tackle the problem of time consumption and accuracy. Three types of blood abnormality have been covered here, namely, anemia which is characterized by low count of red blood cells (RBCs), Leukemia which is depicted by increasing the number of white blood cells (WBCs), and sickle cell blood disorder which is caused by a deformation in the shape of red cells. The algorithm has been tested on different images of blood smears and noticed to give an acceptable level of accuracy. Image processing techniques has been used here to detect the different types of blood constituents. Unlike many other researches, this research includes the blood sickling disorder which is epidemic in certain regions of the world, and offers a more accuracy than other algorithms through the use of detaching overlapped cells strategy.</span>

Detection of Sickle Cell Anemia Through Contour Evidence Extraction and Estimation

Diagnosis of sickle cell anemia by manual visual inspection through microscope is time consuming and causes human errors. Observational errors occur mostly due to overlapping of cells in blood smear image. Here, an automatic segmentation approach is introduced which isolates sickle cells from all other cells within a blood sample. The proposed system is an approach to find the elliptically shaped sickle cells through geometric feature extraction and contour based segmentation to isolate sickle cells. This technique is a method of isolating sickle cells from other cells within blood sample using cell morphology. A combined approach of extraction of seed points, contour extraction and estimation of contours is used for separation of sickle cells from red blood cells. The methods used for the extraction of seed points are by Ultimate Erosion for Convex Sets and Fast Radial Symmetry transform. The contour evidence is extracted by associating edges of the cells to the seed points. The overlapping and clustered cells in image are identified using ellipse fitting method for contour estimation. Using the seed points and the contour extraction, the edges of the cells are estimated. The lines joining the shape of cells are drawn through estimation of shape of contour. This eliminates cells other than elliptical shaped cells. The proposed system can successfully isolate sickle cells from healthy blood cells within the blood smear image. This automated system has a better accuracy and faster computation speed compared to the existing methods for the detection of sickle cells. This identification methodology helps the health professionals for faster diagnosis.

A 24-Year-Old Woman First Diagnosed as a Sickle Cell Anemia during her Second Pregnancy: A Case Report

Introduction: Sickle cell anemia (SCA) is generally diagnosed in the early childhood and the disease is usually diagnosed in the first years of life by its clinical manifestations. The crises of this disease worsens during pregnancy. In this report, a 24-year-old pregnant woman with gestational age of 29 weeks and six days, G2P2A0L1, is presented. She complained of severe back and lower extremity pain. Considering the refractory pain, severe anemia, and absence of delivery process signs, further tests detected SCA for her. Preterm termination of pregnancy were performed by cesarean section regarding severe non-controlled pain, severe IUGR (intrauterine growth retardation), severe oligohydramnios, and previous caesarian section. A female baby was born with Apgar score of 8 and a birth weight of 1250 grams. Considering the high probability of vascular occlusion crisis and severe anemia associated with SCA during pregnancy, it is reasonable to seek sickle cells in all the pregnant patients with severe unexplained anemia or pain.

Identification of Sickle Cell Anemia Using Deep Neural Networks

A molecule called hemoglobin is found in red blood cells that holds oxygen all over the body. Hemoglobin is elastic, round, and stable in a healthy human. This makes it possible to float across red blood cells. But the composition of hemoglobin is unhealthy if you have sickle cell disease. It refers to compact and bent red blood cells. The odd cells obstruct the flow of blood. It is dangerous and can result in severe discomfort, organ damage, heart strokes, and other symptoms. The human life expectancy can be shortened as well. The early identification of sickle calls will help people recognize signs that can assist antibiotics, supplements, blood transfusion, pain-relieving medications, and treatments etc. The manual assessment, diagnosis, and cell count are time consuming process and may result in misclassification and count since millions of red blood cells are in one spell. When utilizing data mining techniques such as the multilayer perceptron classifier algorithm, sickle cells can be effectively detected with high precision in the human body. 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. This paper also presents the precision degree of the MLP classifier algorithm with other popular mining and machine learning algorithms on the dataset obtained from the Thalassemia and Sickle Cell Society (TSCS) located in Rajendra Nagar, Hyderabad, Telangana, India. Doi: 10.28991/esj-2021-01270 Full Text: PDF

Pathophysiological Relevance of Renal Medullary Conditions on the Behaviour of Red Cells From Patients With Sickle Cell Anaemia

Red cells from patients with sickle cell anaemia (SCA) contain the abnormal haemoglobin HbS. Under hypoxic conditions, HbS polymerises and causes red cell sickling, a rise in intracellular Ca2+ and exposure of phosphatidylserine (PS). These changes make sickle cells sticky and liable to lodge in the microvasculature, and so reduce their lifespan. The aim of the present work was to investigate how the peculiar conditions found in the renal medulla – hypoxia, acidosis, lactate, hypertonicity and high levels of urea – affect red cell behaviour. Results show that the first four conditions all increased sickling and PS exposure. The presence of urea at levels found in a healthy medulla during antidiuresis, however, markedly reduced sickling and PS exposure and would therefore protect against red cell adherence. Loss of the ability to concentrate urine, which occurs in sickle cell nephropathy would obviate this protective effect and may therefore contribute to pathogenesis.

Effect of Rhynchospora corymbosa and Olax subscorpioïdea two plants used in the management of Korhogo sickle cell disease

Sickle cell disease is the first genetic disease in the world. Rhynchospora corymbosa and Olax subscorpioïdea are two plant species used in traditional management of sickle cell disease in the department of Korhogo. After a chemical study of the decocted and the aqueous extract of these two plants, their effect on the in vitro reversal of sickling of HbSS genotype erythrocytes, has been evaluated according to Emmel method. An abundance of alkaloids, tannins, saponins, polyterpenes and sterols was found in the decocted and aqueous extract of Rhynchospora corymbosa (DRC and MRC). As for the decocted and aqueous extract of Olax subscorpioïdea (DOSA and MOSA), polyphenols, leucoanthocyanins and flavonoids were found in addition to the chemical compounds identified in Rhynchospora corymbosa. At the concentration of 0.312 mg/mL DRC, MRC DOSA and MOSA have obtained the reversal rate of 75, 50, 80 and 80% respectively. All four extracts demonstrated activity on in vitro reversal of sickle cells. This activity could be caused by the presence of chemical groups that would be used in the treatment of several diseases because of their anti-oxidant and anti-inflammatory properties. Rhynchospora corymbosa and Olax subscorpioïdea are both an effect on the in vitro sickling reversal. Their use in the management of sickle cell disease in northern Côte d'Ivoire might be justified.

HENNA (Lawsonia inermis) A MEDICINAL HERB EFFECTIVE IN SICKLE CELL DISEASE

Sickle cell anemia is a common disease in Oman country. In this disease, sickle-shaped cells are formed. These cells interrupt blood vessels and cause a reduction in oxygen transportation. It was founded that henna (Lawsonia inermis) can prohibit the formation of sickle cells. The Lawsone (2-Hydroxy-1,4-Naphthoquinone) is the constituents of henna which is responsible for the anti-sickling activity, by increasing the oxygen affinity of red blood cells. Hena has the anti-sickling activity which is proved by incubating aqueous and methanolic henna extracts with sickle cell disease patient's whole blood. Then for reduction to oxygen tension 2%, sodium bisulphite was added. Therefore, the percentage of sickled cells to normal red blood cells was observed at 30 minutes intervals. Henna proved a delay in the sickling process in 84% of the tested samples. Both extracts(aqueous and methanolic henna) can delay sickling for about an hour.

Deep Vein Thrombosis and Pulmonary Embolism in Sickle Cell Disease

Sickle Cell Disease (SCD) is considered a group of genetic red blood cell (RBC) disorders. Healthy red blood cells (RBC) are round in shape and migrates throughout the body to carry oxygen in the small blood vessels. In SCD, the RBC turns into hard and sticky, and the shape is similar to a C-Shaped tool called "SICKLE." Because of the early death of the sickle cells, a constant shortage of red blood cells arises. Because of the typical shape of the sickle cells, their movement in the blood vessel is not as smooth as normal RBC and get stuck and clog the blood flow leading to anemia. The changes in shape make the cells more easily destroyed, causing anemia. Defective hemoglobin is the primary cause of SCD.

Yoda1 and phosphatidylserine exposure in red cells from patients with sickle cell anaemia

Phosphatidylserine (PS) exposure is increased in red cells from sickle cell anaemia (SCA) patients. Externalised PS is prothrombotic and attractive to phagocytes and activated endothelial cells and thus contributes to the anaemic and ischaemic complications of SCA. The mechanism of PS exposure remains uncertain but it can follow increased intracellular Ca2+ concentration ([Ca2+]i). Normally, [Ca2+]i is maintained at very low levels but in sickle cells, Ca2+ permeability is increased, especially following deoxygenation and sickling, mediated by a pathway sometimes called Psickle. The molecular identity of Psickle is also unclear but recent work has implicated the mechanosensitive channel, PIEZO1. We used Yoda1, an PIEZO1 agonist, to investigate its role in sickle cells. Yoda1 caused an increase in [Ca2+]i and PS exposure, which was inhibited by its antagonist Dooku1 and the PIEZO1 inhibitor GsMTx4, consistent with functional PIEZO1. However, PS exposure did not necessitate an increase in [Ca2+]i. Two PKC inhibitors were also tested, chelerytherine chloride and calphostin C. Both reduced PS exposure whilst chelerytherine chloride also reduced Yoda1-induced increases in [Ca2+]i. Findings are therefore consistent with the presence of PIEZO1 in sickle cells, able to mediate Ca2+ entry but that PKC was also involved in both Ca2+ entry and PS exposure.