source code for blood group detection in matlab

Abstract

Blood cancer is the most prevalent and it is very dangerous among all types of cancer. Early identification of blood cancer is the ability to reduce mortality and disorder. There are many clinical techniques and tests to detect blood cancer. Although many of these tests are extremely complex and subjective and are heavily dependent on the technician's experience. To remove these problems, image processing techniques and a fuzzy conclusion system, in this study, use methods for the detection of different types of blood cancer. The accuracy rate of diagnosis of blood cancer by using the fuzzy system will give a slightly higher rate of accuracy after other conventional methods and will reduce effort and time. We first make the initial discussion of cell biology necessary to move forward to implement our proposed method. In this project, a given picture of patient's cancer-affected blood sample has been presented with a new automatic approach to detect and analyze blood cancer. The proposed method is using waveform transformation for image correction, splitting different cells of the blood to detect image segmentation, range detection, size and shape of cells to detect edge and finally fuzzy indorens Systems, different cells