An improved pre-processing technique with image mining approach for the medical image (Found in Endoscope) classification. Rational and Significance The proposed system mainly concentrates on the diagnosis of Endoscope Images . This work gives the Endoscope Surgeons a second option for the easy identification of interior images of esophagi. The important data mining concept that has been included in the proposed work consists of pre-processing of the Endoscope Images. The method used for pre-processing includes Shape priori technique.
The feature selection from the image has been done using the association rule mining. The rules enervated for extracted features are stored in the transactional database have been classified using the data mining concept called Decision Tree Classification. The combination of both the association rule mining and the decision tree classification gives the high degree of accuracy and efficiency for the proposed system. Literature Review 1 . A data mining algorithmic approach for processing wireless capsule endoscope data sets (Agrarians, A. ; Bourbon’s, N.
Engineering in Medicine and Biology Society, 2009. EMBED 2009. Annual International Conference of the IEEE ) Wireless capsule endoscope (WEEK) has been a breakthrough n recent medical technology. It is used to view the gastrointestinal tract and detect abnormalities such as bleeding, Crown’s disease, peptic ulcers, and colon cancer. In this paper data mining techniques are utilized to extract useful information from a dataset of abnormal regions and non-abnormal regions. More specifically, the dataset contains polyps regions, ulcers regions and healthy regions.
A number of features (shape descriptors, texture descriptors and color information) has been extracted for these regions and using a data mining toolbox useful conclusions are given on various relationships between these regions. 2. Research and application of CT image mining based on rough sets theory and association rules (Xx Dong; Lie Fun Computer Science and Information Technology (CCITT), 2010 3rd IEEE International Conference on ) The function of medical image mining in computer-aided diagnoses is discussed.
Aiming at the hospital of valuable CT images, combining medical peculiar domain knowledge, a kind of association rules based on rough sets and combination of mining method is proposed, this method can help doctors early diagnose malignant diseases and has a great significance. 3. An improved pre-processing technique with image mining approach for the deiced image classification (Regenerated, P. ; Maidenheads, M. ; Incarnadining, K.
Computing Communication and Networking Technologies ) The proposed system mainly concentrates on the diagnosis of brain tumor from the CT-Scan (Computerized Tomography) brain images. This work gives the neurologist’s a second option for the easy identification of tumor cells from the brain image. The important data processing of the CT-Scan brain image. The method used for pre-processing includes Shape priori technique. The feature selection from the brain image has been done using the association rule mining.
The rules generated for extracted features are stored in the transactional database have been classified using the data mining concept called Decision Tree Classification. The combination of both the association rule mining and the decision tree classification gives the high degree of accuracy and efficiency for the proposed system. Aims And Objectives 1. Develop a tool to identification identify the diseases. 2. To discovers hidden patterns in the data Scope of study There is vast scope for this study . Once the study is being started then we will able to predict the things on the real ground. Research methodology Primary Data The primary data for the study collected by performing the retrieval of data from the repository and after that doing the observations. Secondary Data The Sources of data are as following Journals Research Papers Books Periodicals Information from various Websites Methodology of Data Collection Primary data collection is required to perform the actual analysis.
Patients data is available in terms of the Text ,photographs and videos . Videos are nothing but the record which interprets the information regarding the treatment as well as diagnosis. In order to store the information . Elated to the patients structures are defined. The secondary data was identified and located by reading thoroughly various text books on the subject and articles published in various magazines ћJournals of professionals bodies. The websites related to the subject were browsed and the required data was identified and located.
The identified secondary data was evaluated to ascertain whether the data identified is pertinent and relevant to the research problem to be addressed. The irrelevant data were discarded and relevant data was taken up. However , before making use of the relevant secondary data its accuracy , reliability and completeness was studied by evaluating the credibility of the organizations and the methodology used by the organization for collection of the data , which published these secondary data.