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# Cancer-test |
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Blood consists of plasma, and three different types of cells and they are: White Blood |
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Cells, Red Blood Cells and Platelets and each of these performs particular task. Red |
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blood cells transport oxygen from the lungs to the tissues of the body and vice versa. |
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White blood cells help the body to fight against diseases and infections. Platelets help |
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to clot and control bleeding. Leukemia is cancer of blood cells in which number of |
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white cells is increases numerously and those are immature cells that interfere with |
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other blood cells, usually red blood cells and platelets. Our body’s white blood cell ratio |
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is 1000:1. It means that between 1000 red blood cells there is 1 white blood cell. |
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There are two types of white blood cells that get turn into leukemia and they are: |
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1. Lymphoid cells |
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2. Myeloid cells |
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Leukemia that caused due to lymphoid cells is called lymphocytic or lymphoblastic |
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leukemia and if it is caused due to myeloid cells then it is known as myelogenous |
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or myeloid leukemia. Leukemia is grouped in two ways: acute or chronic, grouped |
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according to how fast the cells are growing. The abnormal blood cells in acute |
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leukemia are usually immature blasts (young cells) that do not work properly. These |
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cells are growing fast. Acute leukemia gets worse quickly unless it is immediately |
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treated. Young blood cells are present in chronic leukemia, but also mature |
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functional cells are produced. Blasts are growing slowly in chronic leukemia. It |
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takes the disease longer to get worse. |
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The four major forms of leukemia are: |
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1. Acute lymphoblastic leukemia (ALL) |
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2. Acute myelogenous leukemia (AML) |
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3. Chronic lymphocytic leukemia (CLL) and |
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4. Chronic myelogenous leukemia (CML) |
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# PURPOSE |
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The purpose of our project is to develop a system that can automatically detect cancer |
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from the blood cell images. This system uses a convolution network that inputs a blood |
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cell images and outputs whether the cell is infected with cancer or not. The appearance |
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of cancer in blood cell images is often vague, can overlap with other diagnoses, and can |
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mimic many other benign abnormalities. These discrepancies cause considerable |
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variability among medical personnel in the diagnosis of cancer. Automated detection |
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of cancer from blood cell images at the level of expert medical personnel would not |
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only have tremendous benefit in clinical settings, it would also be invaluable in delivery |
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of health care to populations with inadequate access to diagnostic imaging specialists. |
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# visit [aihubprojects.com](https://aihubprojects.com/blood-cancer-detection-using-cnn-ai-projects/) for more |