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