@article{Arumbaka Srinivasa Rao,Dr S V N Srinivasu,PGayatri, DAnand_2020, title={Development of Expert System for Bone Cancer detection}, volume={29}, url={http://sersc.org/journals/index.php/IJAST/article/view/27269}, abstractNote={<p><em>Now a day’s cancer is becoming one of the major diseases in all over the world. Due to several regions it is attacking to all age of persons. By going through different kinds of researchers almost there are more than 100 kinds of cancers has been found in human body it may affect. Out of those cancers one most dangerous one is bone cancer which will leads to death as soon as it attacks to body. In this paper we are going to use some image processing techniques to detect the bone cancer. Medical imaging is taking a significant task in diagnosing, handling of ailment, locating tumours and recognition of malignancy cells in premature periods. For finding bone features, a traditional method called microscopic images are used. By using micro radiography, this images are produced which is used for repeated, labour- intensive and time consuming process.This method is not satisfactory to deal little resolution and interrupted pictures. For this reason, there is a necessity for automatic and consistent systems to perform the image handling study.</em></p> <p><em>In our case we have chosen bone tumour to screen and identify the bone tumour rather the other connective tissue since the outgrowth are lumps which can be predict easier. This tissue contains three types of cells- osteoblasts, osteoclasts and osteocytes. A bone cancer is an uncontrolled growth of bone cells. Anomalous developments originated in the bone may survive as either benign (benevolent or noncancerous) or malignant (harmful or destructive). Our aim is to screen and identify the bone tumour in the initial stage using image processing</em><strong><em>.</em></strong></p&gt;}, number={7}, journal={International Journal of Advanced Science and Technology}, author={Arumbaka Srinivasa Rao,Dr S V N Srinivasu,PGayatri, DAnand}, year={2020}, month={Jun.}, pages={10733-10737} }