EXTRACTION OF TEXTURE FEATURES IN CYTOPATHOLOGY
Journal: International Journal of Electrical Engineering and Technology (IJEET) (Vol.11, No. 10)Publication Date: 2020-12-31
Authors : D. Paulin Diana Dani A. Senthil Arumugam;
Page : 291-305
Keywords : Micrograph; Cervical Cyto; Cancer Cell Analysis;
- LITERATURE SURVEY ON MACHINE LEARNING WITH INTERNET OF THINGS (IOT)
- A Literature Survey on Internet of Things (IoT)
- A STUDY OF USE OF INTERNET OF THINGS AND MACHINE LEARNING IN SMART WASTE MANAGEMENT
- MACHINE LEARNING TECHNIQUES TO DETECT ROUTING ATTACKS IN RPL BASED INTERNET OF THINGS NETWORKS
- Energy Smart Meter operation improved by Machine Learning’s Decision-Support System and Internet Of Things
Abstract
An image processes diverse features, which reveals a lot of information about the object itself. Similarly, medical images also possess diverse features like color, texture, shape, spatial location etc., through which I come to know whether it is diseased or not. In this paper I have set out to find out which of the various texture features is best in detecting the cancer. The cancer taken for scrutiny is cervical cancer. The reason behind choosing this cancer is mainly attributed to the cause that this is the most deadly form of cancer and is the cause of millions of deaths among women worldwide. Here I have studied and analyzed certain texture features and tried to find out which is best in detecting the cancer or not
Other Latest Articles
Last modified: 2021-03-04 21:36:45