Blood cancer is an uprising issue and doing physical medical procedures is too sensitive and time-consuming to detect any blast cell. Manual testing includes blood tests, spinal fluid tests, bone marrow tests, imaging tests, etc. A solution to this is to use modern methods in health care that help to detect diseases faster and increase the cure rate.ssing and Transfer Learning for Detection of Types of Leukemia: In image processing, data preparation and image preprocessing are done where we have rescaled the image and adjusted the brightness to improve the image quality. Data augmentation is performed to increase the image count by flipping it horizontally and vertically. Images are converted to grayscale to reduce the matrix calculation.The images in the dataset are: AML has 935 images, ALL has 858, CML has 623 and CLL has 510. Transfer learning is used. I have used different pre-trained CNN models such as ResNet-50, VGG16, Inception V3, and MobileNet for feature extraction and classification.VGG16, InceptionV3 and MobileNet - all three models give 100% accuracy, while ResNet50 gives 85% accuracy.

A disease is a particular abnormal condition that negatively affects the structure or function of all or part of an organism, and that is not due to any immediate external injury. In humans, disease is often used more broadly to refer to any condition that causes pain, dysfunction, distress, social problems, or death to the person afflicted, or similar problems for those in contact with the person. Diseases such as Cancer is one which is having high mortality rate. Cancer is a disease in which some of the body’s cells grow uncontrollably and spread to other parts of the body causing death. Cancer is very hard to predict and if not predicted on time can be fatal. The technology today is very advanced and fast. Most cancer diseases like breast cancer can be predicted. Yet there are more of cancers which cannot be predicted at an early stage or till 3rd or 4th stage of disease, Such as Lung cancer, Colon Cancer, Leukaemia (Blood Cancer). Here in our project, we are trying to analyse Leukemia a patient is having by using a medical image. In our project “Leukemia Detection using Inception V3” we will be using microscopic images of WBC of the patients having Leukaemia of ALL type. With the help of DL methodologies, we will analyse the images and use them to train our model which will eventually predict whether the patient is having ALL, when a new image is given as input to the model. The scope of our project is very general and only for research purpose. Till now we are just focusing of how to use Deep Learning techniques to analyses an image and further train a model using images to predict leukemia. On a long-term perspective, we will surely try to take this project to next level where cancer will be predicted on early stage and in real time.