Medical Image Analysis and Classification for Varicose Veins
Jyoti Yogesh Deshmukh, Vijay U. Rathod, Yogesh Kisan Mali, Rachna Sable
Abstract
The medical field needs a lot of data in the form of images and text to diagnose the disease correctly. Data science is providing many faster analytical methods which are helpful in many decisions related to medication or precautions. Varicose veins are a disease caused by twisted or enlarged veins in the leg, which are blackish or blueish. Diagnosing the twists and blockages, it needs a test like colour Doppler ultrasound. This test gives clear images of where exactly the blood is flowing in opposite directions in the legs. Medical image analysis and classification involve different tasks to be performed in sequence to assist specialists in diagnosing diseases efficiently and effectively. Convolutional neural network (CNN) is used to more accurately analyse colour Doppler ultrasound test results. Medical image segmentation is one more invention in data science that provides much better results in understanding the complexity of twists in the veins. Data science has given hope to many patients suffering from this disease for faster diagnosis and recovery of varicose veins treatment as a cosmetic purpose solution. It majorly uses laser treatment for a less surgical approach.