Modified Dominance-based soft set Approach for Feature Selection

Big data analysis applications in the field of medical image processing have recently increased rapidly. Feature reduction plays a significant role in eliminating irrelevant features and creating a successful research model for Big Data applications. Fuzzy clustering is used for the segment of the nucleus. Various features, including shape, texture, and color-based features, have been used to address the segmented nucleus. The Modified Dominance Soft Set Feature Selection Algorithm (MDSSA) is intended in this paper to determine the most important features for the classification of leukaemia images. The results of the MDSSA are evaluated using the variance analysis called ANOVA. In the dataset extracted function, the MDSSA selected 17 percent of the features that were more promising than the existing reduction algorithms. The proposed approach also reduces the time needed for further analysis of Big Data. The experimental findings confirm that the performance of the proposed reduction approach is higher than other approaches.

Threshold Estimation Based on Local Minima for Nucleus and Cytoplasm Segmentation

Background: Image segmentation is a process of partitioning the input image into its separate objects or regions. It is an essential step in image processing to segment the regions of interest (ROI) for further processing. We propose a method for segmenting neucleus and cytoplasm from the white blood cells (WBC).Methods: Initially, the method computes an initial value based on the minimum and maximum values of the input image. Then, a histogram of the input image is computed and then approximated to obtain function values. The method searches for the first local maximum and local minimum from the approximated function values. We approximate the required threshold from the first local minimum and the computed initial value based on defined conditions. The threshold is applied to the input image to binarize it and then perform post-processing to obtain the final segmented nucleus. We segment the whole WBC before segmenting the cytoplasm depending on the complexity of the objects in the image. For WBCs which are well separated from the RBCs, n thresholds are generated and then produce n thresholded images. Then, a standard Otsu method is used to binarize the average of the produced images. Morphological operations are applied on the binarized image and then use a single-pixel point from the segmented nucleus to segment the WBCs. For images in which RBCs touch the WBCs, we segment the whole WBC using SLIC and watershed methods. The cytoplasm is obtained by subtracting the segmented nucleus from the segmented WBC. Results: The method is tested on two different public data sets. Performance analysis is done and the results show that the proposed method segments well the nucleus and cytoplasm. Conclusion: We propose a method for nuclei and cytoplasm segmentation based on the local minima of the approximated function values from the histogram of image. The method has demonstrated its utility in segmenting nuclei, WBCs and cytoplasm and the results are reasonable.

DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set

Diffuse Large B-Cell Lymphoma (DLBCL) is the most common non-Hodgkin lymphoma. Though histologically DLBCL shows varying morphologies, no morphologic features have been consistently demonstrated to correlate with prognosis. We present a morphologic analysis of histology sections from 209 DLBCL cases with associated clinical and cytogenetic data. Duplicate tissue core sections were arranged in tissue microarrays (TMAs), and replicate sections were stained with H&E and immunohistochemical stains for CD10, BCL6, MUM1, BCL2, and MYC. The TMAs are accompanied by pathologist-annotated regions-of-interest (ROIs) that identify areas of tissue representative of DLBCL. We used a deep learning model to segment all tumor nuclei in the ROIs, and computed several geometric features for each segmented nucleus. We fit a Cox proportional hazards model to demonstrate the utility of these geometric features in predicting survival outcome, and found that it achieved a C-index (95% CI) of 0.635 (0.574,0.691). Our finding suggests that geometric features computed from tumor nuclei are of prognostic importance, and should be validated in prospective studies.

Age dynamics of hematological indices in dry cows

The requirement for the study of blood parameters is determined by its physiological significance and changes that occur in different physiological and pathological conditions. The hematological profile is an important criterion that shows the physiological condition of animals. The physiological changes of blood in cows have been established concerning the conditions of keeping and feeding, hygienic parameters, in the dynamics of the dry season, in different seasons of the year, etcetera. We have not found any information on studies of the dynamics of blood parameters in pregnant animals, depending on their age, in the study of literary sources in recent years. The purpose of our work was to study the age-related dynamics of hematological blood parameters in cows during the dry period. Our studies aimed to determine the hematological indices of Holstein breed cows in the physiological course of the prenatal period during the dry period, depending on the number of deep calving. Control and experimental groups were formed on the principle of group-analogues (by breed, age, sex, physiological state, weight, milk productivity). Animals kept in typical rooms with satisfactory microclimate parameters (in winter) and at camps (in summer). Laboratory studies were carried out in the laboratory of the Dnipro State Agrarian and Economic University. Hematologic studies were performed according to the following indicators: erythrocytes, hemoglobin, color index, erythrocyte sedimentation rate, leukocytes, monocytes, lymphocytes, neutrophils with rod-like shape and segmented nucleus, basophils and eosinophils according to conventional methods. The results of our studies indicate that the lowest number of erythrocytes was detected in the cows of the sixth calving and the highest hemoglobin content, which led to the rise of the color index – in cows of the fifth pregnancy present the reverse tendency; increase to the maximum values of the number of leukocytes in cows of the third body (1.32 times), which is a reflection of the greater reactivity of the body of cows of this age group; a probable decrease (by 10.59 %, P < 0.05) of lymphocyte counts was found in sixth-calf cows, indicating a weakened immune response; also increased eosinophils almost 1.75 times (P < 0.05) compared to fifth pregnancy; the trend of a gradual decrease in the number of segmented neutrophils in calving cows is followed by a second to fifth pregnancy and a significant reduction in the number of stab neutrophils in cows of the fifth pregnancy of up to 1.33 %.

Granulocytes in health and disease

White cells (leucocytes) mediate inflammatory and immune responses and are key to the defence of the host against microbial pathogens. Subpopulations of leucocytes include granulocytes—neutrophils, eosinophils, and basophils; monocytes; and lymphocytes. Neutrophils comprise half the peripheral circulating leucocytes and are characterized by heterogeneous primary and secondary granules and a segmented nucleus. Maturation from the haematopoietic stem cell occurs in the bone marrow and takes 10 to 14 days. Neutrophilia—defined as an increase in the circulating neutrophil count to greater than 7.5 × 106/µl, usually occurs as an acquired reactive response to underlying disease. Causes include infection, particularly bacterial; drugs; malignancies, and hereditary conditions. Neutropenia—defined as a reduction in the absolute neutrophil count to less than 1.5 × 106/µl, is of particular importance because, when severe (<0.5 × 106/µl), it markedly increases the risk of life-threatening infection. Causes include drugs and toxins, postinfectious, nutritional deficiencies, autoimmune, large granular lymphocytosis, and congenital. Disorders of neutrophil function include chronic granulomatous disease, leucocyte adhesion deficiency, myeloperoxidase deficiency, and Chediak–Higashi syndrome. Monocytes share a common myeloid precursor with granulocytes, present antigens to T cells, produce several important cytokines with immunomodulatory and inflammatory functions, and are the precursors to resident tissue macrophages. They are especially important in defence against intracellular pathogens. Causes of monocytosis (>0.9 × 106/µl) include chronic infection, autoimmune diseases, and malignancy. Basophils are nonphagocytic granulocytes that function in immediate-type hypersensitivity. Basophilia (> 0.2 × 106/µl) is seen in myeloproliferative disorders, hypersensitivity reactions, and with some viral infections.

Human CD62Ldim neutrophils identified as a separate subset by proteome profiling and in vivo pulse-chase labeling

During acute inflammation, 3 neutrophil subsets are found in the blood: neutrophils with a conventional segmented nucleus, neutrophils with a banded nucleus, and T-cell–suppressing CD62Ldim neutrophils with a high number of nuclear lobes. In this study, we compared the in vivo kinetics and proteomes of banded, mature, and hypersegmented neutrophils to determine whether these cell types represent truly different neutrophil subsets or reflect changes induced by lipopolysaccharide (LPS) activation. Using in vivo pulse-chase labeling of neutrophil DNA with 6,6-2H2-glucose, we found that 2H-labeled banded neutrophils appeared much earlier in blood than labeled CD62Ldim and segmented neutrophils, which shared similar label kinetics. Comparison of the proteomes by cluster analysis revealed that CD62Ldim neutrophils were clearly separate from conventional segmented neutrophils despite having similar kinetics in peripheral blood. Interestingly, the conventional segmented cells were more related at a proteome level to banded cells despite a 2-day difference in maturation time. The differences between CD62Ldim and mature neutrophils are unlikely to have been a direct result of LPS-induced activation, because of the extremely low transcriptional capacity of CD62Ldim neutrophils and the fact that neutrophils do not directly respond to the low dose of LPS used in the study (2 ng/kg body weight). Therefore, we propose CD62Ldim neutrophils are a truly separate neutrophil subset that is recruited to the bloodstream in response to acute inflammation. This trial was registered at www.clinicaltrials.gov as #NCT01766414.

A comparative histological study on the blood film of young and adult, male and female Monkeys (Chlorocebus pygerythrus)

Twenty Vervets monkeys were used to study the effect of sexes and ages on morphohistological and hematological pictures. The study revealed that age and sex affect blood values. Vervet monkeys registered a significant dominancy of hematological parameters in adult males. Erythrocytes of vervet monkeys were of macrocytic type, howell-Jolly bodies were observed. Rouleaux formation, Anisocytosis, Aggregation, and Agglutination were not observed. A significant predominancy of neutrophils in females and lymphocytes in males was recorded. The neutrophil was well defined, large with ring-shaped highly segmented nucleus. Band neutrophils were not observed in peripheral blood. Eosinophils recorded high values. Circulating leukocytes acted as a transient phase in the functional development of tissue leukocytes. Lymphocytes were the most common cells among leukocytes. Three sizes of lymphocytes and two of monocytes were registered. The value of monocytes percent was higher in males. The herein study declared that blood platelets showing different sizes, shapes and affinities for basic stains and according to these functional affinity, light resting and dark stimulating blood platelets were classified. There was a reverse relationship between the number of erythrocytes and blood platelets among different sexes and ages. In conclusion, the present study hypothesized that blood platelets serve as a supporting cells for blood cells especially erythrocytes. Besides, humoral immune defense in monkeys were well developed.

Unsupervised Leukocyte Image Segmentation Using Rough Fuzzy Clustering

The segmentation of leukocytes and their components acts as the foundation for all automated image-based hematological disease recognition systems. Perfection in image segmentation is a necessary condition for improving the diagnostic accuracy in automated cytology. Since the diagnostic information content of the segmented images is plentiful, suitable segmentation routines need to be developed for better disease recognition. Clustering is an essential image segmentation procedure which segments an image into desired regions. A judicious integration of rough sets and fuzzy sets is suitably employed towards leukocyte segmentation in a clustering framework. In this study, the goodness of fuzzy sets and rough sets is suitably integrated to achieve improved segmentation performance. The membership concept of fuzzy sets endow is efficient handling of overlapping partitions, and the rough sets provide a reasonable solution to deal with uncertainty, vagueness, and incompleteness in data. Such synergistic combination gives the proposed scheme an edge over standard cluster-based segmentation techniques, that is, K-means, K-medoid, fuzzy c-means, and rough c-means. Comparative analysis reveals that the hybrid rough fuzzy c-means algorithm is robust in segmenting stained blood microscopic images. The accomplished segmented nucleus and cytoplasm of a leukocyte can be used for feature extraction which leads to automated leukemia detection.

Quantitative 3d Analysis Of Intra-Nuclear Organization In The Tissue Context

Confocal microscopy is revealing associations between the internal organization of the nucleus and tissue architecture and function. Such associations may exist which are too subtle or complex for visual observation or quantitative analysis may be required, for example as input data to mathematical modeling of cellular processes. In these circumstances, it is necessary to perform the analysis using computer algorithms. We have developed 3D image analysis (IA) algorithms for segmenting nuclei from within intact tissue specimens, measuring the structure of the nuclei and for segmenting specifically- labeled punctate entities within nuclei. In this study we developed algorithms for measuring the spatial organization of the two copies of a specific DNA locus (labeled using fluorescence in situ hybridization (FISH) ) inside diploid nuclei and with respect to the nuclear organization of the tissue.For each segmented nucleus, its center of mass (CoM) was determined, which informed us about its position in the tissue.