Comparative analysis of filtering methods in fuzzy C-means: environment for DICOM image segmentation

D. Nagarajan, D. Nagarajan and Jacobb, Kavikumar and Mustapha, Aida and Boppana, Udaya Mouni and Chaini, Najihah (2021) Comparative analysis of filtering methods in fuzzy C-means: environment for DICOM image segmentation. In: Generative adversarial networks for image-to-image translation. Elsevier, pp. 81-98. ISBN 978-0-12-823519-5

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Medical image analysis was done using a sequential application of low-level pixel processing and mathematical modeling to develop rule-based systems. During the same period, artificial intelligence was developed in analogy systems. In the 1980s magnetic resonance or computed tomography imaging system has been introduced that encode and decode the output of the images. Digital imaging and communications in medicine (DICOM) has improved the communication mechanism in the medical environment. In products such as CT, MR, X-ray, NM, RT, US, etc., DICOM is used for image storing, printing the information about the patient’s condition, and transmitting the correct information about the radiological images. It involves a file format and protocol in communication networks. It is useful for receiving images and patient data in DICOM format. DICOM format has been widely adopted to all medical environments and derivations from the DICOM standard are used into other application areas. DICOM is the basis of digital imaging and communication in nondestructive testing and in security. DICOM data consist of many attributes including information such as name, ID, and image pixel data. A single DICOM object can have only one attribute containing pixel data. Pixel data can be compressed using a variety of standards, including JPEG, JPEG Lossless, JPEG 2000, and Run-length encoding.

Item Type: Book Section
Uncontrolled Keywords: nil
Subjects: T Technology > TD Environmental technology. Sanitary engineering
Divisions: Faculty of Applied Science and Technology > Department of Technology and Natural Resources
Depositing User: Mr. Abdul Rahim Mat Radzuan
Date Deposited: 13 Jan 2022 00:35
Last Modified: 13 Jan 2022 00:35

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