Development and study of a method for cell separation during white blood cell segmentation on images of bone marrow preparations in information and measurement systems for diagnostics of acute leukemia

2020 ◽  
pp. 68-72
Author(s):  
V.G. Nikitaev ◽  
A.N. Pronichev ◽  
V.V. Dmitrieva ◽  
E.V. Polyakov ◽  
A.D. Samsonova ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Blood Cell ◽  
Acute Leukemia ◽  
White Blood Cell ◽  
Cell Separation ◽  
Large Scale ◽  
Bone Marrow Cells ◽  
Automated Analysis ◽  
Cell Segmentation ◽  
Measurement Systems

The issues of using of information and measurement systems based on processing of digital images of microscopic preparations for solving large-scale tasks of automating the diagnosis of acute leukemia are considered. The high density of leukocyte cells in the preparation (hypercellularity) is a feature of microscopic images of bone marrow preparations. It causes the proximity of cells to eachother and their contact with the formation of conglomerates. Measuring of the characteristics of bone marrow cells in such conditions leads to unacceptable errors (more than 50%). The work is devoted to segmentation of contiguous cells in images of bone marrow preparations. A method of cell separation during white blood cell segmentation on images of bone marrow preparations under conditions of hypercellularity of the preparation has been developed. The peculiarity of the proposed method is the use of an approach to segmentation of cell images based on the watershed method with markers. Key stages of the method: the formation of initial markers and builds the lines of watershed, a threshold binarization, shading inside the outline. The parameters of the separation of contiguous cells are determined. The experiment confirmed the effectiveness of the proposed method. The relative segmentation error was 5 %. The use of the proposed method in information and measurement systems of computer microscopy for automated analysis of bone marrow preparations will help to improve the accuracy of diagnosis of acute leukemia.

White Blood Cell Segmentation for Acute Leukemia Bone Marrow Images

2012 ◽  
Vol 2 (3) ◽  
pp. 278-284 ◽  
Author(s):  
Lim Huey Nee ◽  
Mohd Yusoff Mashor ◽  
Rosline Hassan
Keyword(s):  
Bone Marrow ◽  
Blood Cell ◽  
Acute Leukemia ◽  
White Blood Cell ◽  
Cell Segmentation

METHODS OF MULTICLASSICATION OF BONE MARROW CELLS FOR THE DIAGNOSIS OF ACUTE LEUKEMIA AND MINIMAL RESIDUAL DISEASE (ON THE MATERIALS OF THE LABORATORY OF HEMATOPOIESIS OF N. N. BLOKHIN NATIONAL MEDICAL RESEARCH CENTER OF ONCOLOGY)

2020 ◽  
pp. 155-158
Author(s):  
Валентина Викторовна Дмитриева ◽  
Николай Николаевич Тупицын ◽  
Евгений Валерьевич Поляков ◽  
Софья Сергеевна Денисюк
Keyword(s):  
Bone Marrow ◽  
Acute Leukemia ◽  
Medical Research ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Binary Classification ◽  
National Medical ◽  
Cell Class ◽  
Minimal Residual ◽  
Marrow Cells

Применение методов и средств цифровой обработки изображений при распознавании типов клеток крови и костного мозга для повышения качества диагностики острых лейкозов является актуальной научно-технической задачей, отвечающей стратегии развития технологий искусственного интеллекта в медицине. В работе предложен подход к мультиклассификации клеток костного мозга при диагностике острых лейкозов и минимальной остаточной болезни. Для проведения экспериментальных исследований сформирована выборка из 3284 изображений клеток, представленных Лабораторией гемопоэза Национального медицинского исследовательского центра онкологии им. Н.Н. Блохина. Предложенный подход к мультиклассификации клеток костного мозга основан на бинарной модели классификации для каждого из исследуемых классов относительно остальных. В рассматриваемой работе бинарная классификация выполняется методом опорных векторов. Метод мультиклассификации был программно реализован с применением интерпретатора Python 3.6.9. Входными данными программы служат файлы формата *.csv с таблицами морфологических, цветовых, текстурных признаков для каждой из клеток используемой выборки. В выборке представлено девять типов клеток костного мозга. Выходными данными программы мультиклассификации являются значения точности классификации на тестовой выборке, которые отражают совпадение прогнозируемого класса клетки с фактическим (верифицированным) классом клетки. “Эксперимент показал следующие результаты: точность мультиклассификации рассматриваемых типов клеток в среднем составила: 87% на тестовом наборе, 88% на обучающем наборе данных. Проведенное исследование является предварительным. В дальнейшем планируется увеличить число классов клеток, объем выборок различных типов клеток и с уточнением результатов мультиклассификации The use of methods and means of digital image processing in the recognition of types of blood cells and bone marrow to improve the quality of diagnosis of acute leukemia is an urgent scientific and technical task that meets the strategy for the development of artificial intelligence technologies in medicine. The paper proposes an approach to the multiclassification of bone marrow cells in the diagnosis of acute leukemia and minimal residual disease. For experimental studies, a sample of 3284 images of cells was formed, submitted by the Hematopoiesis Laboratory of the National Medical Research Center of Oncology named after V.I. N.N. Blokhin. The proposed approach to the multiclassification of bone marrow cells is based on a binary classification model for each of the studied classes relative to the others. In the work under consideration, binary classification is performed by the support vector machine. The multiclassification method was implemented programmatically using the Python 3.6.9 interpreter. The input data of the program are * .csv files with tables of morphological, color, texture features for each of the cells of the sample used. The sample contains nine types of bone marrow cells. The output data of the multiclassification program are the classification accuracy values on the test sample, which reflect the coincidence of the predicted cell class with the actual (verified) cell class. “The experiment showed the following results: the accuracy of multiclassification of the considered types of cells on average was: 87% on the test set, 88% on the training data set. This study is preliminary. In the future, it is planned to increase the number of classes of cells, the volume of samples of various types of cells and with the refinement of the results of multiclassification

A novel framework for white blood cell segmentation based on stepwise rules and morphological features

2011 ◽  
Author(s):  
Ja-Won Gim ◽  
Junoh Park ◽  
Ji-Hyeon Lee ◽  
ByoungChul Ko ◽  
Jae-Yeal Nam
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Morphological Features ◽  
Cell Segmentation

scholarly journals Determination of Advanced Oxidation Protein Products, E3 SUMO-Protein Ligase NSE2[NSMCE2], as a Marker to Predict Child Acute Lymphoblastic Leukemia

2014 ◽  
Vol 11 (1) ◽  
pp. 128-138 ◽  
Author(s):  
Baghdad Science Journal
Keyword(s):  
Bone Marrow ◽  
Acute Lymphoblastic Leukemia ◽  
Blood Cell ◽  
White Blood Cell ◽  
Total Protein ◽  
Lymphoblastic Leukemia ◽  
Advanced Oxidation ◽  
Control Group ◽  
Advanced Oxidation Protein Products ◽  
Sumo Protein

Acute lymphoblastic leukemia (ALL) is a cancer of the blood and bone marrow (spongy tissue in the center of bone). In ALL, too many bone marrow stem cells develop into a type of white blood cell called lymphocytes. These abnormal lymphocytes are not able to fight infection very well. The aim of this study was to investigate possible links between E3 SUMO-Protein Ligase NSE2 [NSMCE2] and increase DNA damage in the childhood patients with Acute lymphoblastic leukemia (ALL). Laboratory investigations including hemoglobin(Hb) ,white blood cell (WBC) , serum total protein , albumin ,globulin , in addition to serum total antioxidant activity (TAA) , Advanced oxidation protein products(AOPP) and E3 SUMO-Protein Ligase NSE2[NSMCE2]. Blood samples were collected from 60 patients diagnosed to Acute lymphoblastic leukemia (ALL) after one month treatment with induction therapy. Age and sex matched 30 healthy persons selected as control.serum total protein , albumin and globulin showed A significant decrease in patients group when compared to control group( P

METHODOLOGY FOR FORMING A DATABASE OF REFERENCE IMAGES OF BONE MARROW CELLS FOR THE AUTOMATED DIAGNOSIS OF ACUTE LEUKEMIA IN ONCOHEMATOLOGY

2021 ◽  
pp. 84-89
Author(s):  
Ольга Александровна Медведева ◽  
Святослав Николаевич Простаков ◽  
Николай Николаевич Тупицын ◽  
Александра Дмитриевна Палладина
Keyword(s):  
Bone Marrow ◽  
Acute Leukemia ◽  
Bone Marrow Cells ◽  
Digital Images ◽  
Automated Image Analysis ◽  
Medical Decision ◽  
Reference Images ◽  
Computer Microscopy ◽  
Marrow Cells

В статье представлено описание факторов, влияющих на качество формирования базы эталонных изображений клеток костного мозга для диагностики острых лейкозов с применением методов компьютерной микроскопии. Отмечена важность контроля качества подготовки препаратов и микроскопа для применения в автоматизированных системах анализа изображений. Рассмотрены особенности регистрации цифровых микроскопических изображений клеток костного мозга в системах компьютерной микроскопии. Исследовано влияние фокусировки оптической системы микроскопа и уровня освещения препарата на формирование цифровых изображений клеток костного мозга. Установлены требования к условиям регистрации цифровых изображений, используемых в автоматизированных системах микроскопического анализа препаратов костного мозга. Предложена концептуальная модель базы эталонных изображений костного мозга, являющаяся основой для разработки инструментов эффективного распознавания клеток костного мозга в системах компьютерной микроскопии. Следование указанным требованиям к регистрации изображений призвано обеспечить надлежащее качество эталонной базы, что имеет непосредственной влияние на повышение точности и достоверности медицинской диагностики с применением методов компьютерной микроскопии. Результаты работы могут быть использованы в системах поддержки принятия врачебных решений при диагностике острых лейкозов The article describes the factors affecting the quality of the formation of a database of reference images of bone marrow cells for the diagnosis of acute leukemia using computer microscopy methods. The importance of quality control of specimen and microscope preparation for use in automated image analysis systems is noted. The features of registration of digital microscopic images of bone marrow cells in computer microscopy systems are considered. The effect of focusing of the optical system of the microscope and the level of illumination of the specimen on the formation of digital images of bone marrow cells is investigated. The requirements for the conditions of registration of digital images used in automated systems of microscopic analysis of bone marrow preparations have been established. A conceptual model of the base of reference images of bone marrow is proposed. It is the basis for the development of tools for effective recognition of bone marrow cells in computer microscopy systems. Following the specified requirements for image registration is designed to ensure the proper quality of the reference base of images, which has a direct impact on improving the accuracy and reliability of medical diagnostics using computer microscopy. The results of the work can be used in medical decision support systems for the diagnosis of acute leukemia

scholarly journals Radioautographic Studies of Bone Marrow Lymphocytes in Vivo and in Diffusion Chamber Cultures

Blood ◽  
1964 ◽  
Vol 23 (1) ◽  
pp. 1-17 ◽  
Author(s):  
D. G. OSMOND ◽  
N. B. EVERETT
Keyword(s):  
Bone Marrow ◽  
Large Scale ◽  
Bone Marrow Cells ◽  
Tritiated Thymidine ◽  
Diffusion Chamber ◽  
Blood Stream ◽  
Turnover Time ◽  
Diffusion Chambers ◽  
Transitional Cells

Abstract Radioautography with tritiated thymidine has been utilized to examine the turnover rate and origin of small lymphocytes in the bone marrow of the guinea-pig. Very few marrow lymphocytes were initially labeled by a single injection of tritiated thymidine, but thereafter the number of labeled lymphocytes rapidly increased to high maximum levels at 3 days. Analysis of the labeling curves and grain counts indicates that the population of marrow lymphocytes is maintained in a dynamic steady state with an average turnover time of 3 days or less. Suspensions of bone marrow cells were isolated from the circulation within intraperitoneal diffusion chambers after short-term labeling with tritiated thymidine in vivo. Although very few small lymphocytes were labeled when introduced into the diffusion chambers, a considerable percentage became labeled during the subsequent culture period. Tritiated thymidine was also administered intravenously whilst excluded from one hind limb by the application of an occlusive compression bandage for 20 minutes. Very few labeled small lymphocytes were found after 72 hours in the tibial marrow of the initially occluded limb, whereas the normal high percentage was labeled in the control tibial marrow. These experiments do not demonstrate any large-scale influx of small lymphocytes from the blood stream into the marrow parenchyma. They suggest that newly formed small lymphocytes appear in the marrow as a result of the division of locally situated precursor cells, but the mechanism of intramedullary lymphocytopoiesis is uncertain. "Transitional" cells, intermediate in morphology between blast cells and small lymphocytes, synthesize DNA and are actively proliferative, but they do not appear to account fully for the rate of lymphocyte production. Certain large, undifferentiated labeled cells appeared in the bone marrow as a result of hematogenous migration. Some implications of these findings are discussed.

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