Search

Advances in imaging technology have made medical images become one of the important sources for information in supporting accurate diagnoses and treatment decisions by doctors for their patients. However, the vulnerability of medical images' security is high. The images can be easily 'attacked', which altered their information that can lead to incorrect diagnoses or treatment. In order to make the images less vulnerable from outside attacks, this study proposes to secure them by advancing the watermarking using dual-layer fragile technique. It is expected that this dual-layer fragile watermarking will guarantee the integrity, authenticity, and confidentiality of patient's and any other important information and also the pixel data of the medical images. The work in this study implements two LSBs of image where the role of the first LSB is as a tamper detector, and the second LSB is used to store patient's and any other important information. Medical images of four deadliest diseases in Indonesia were used to test the proposed watermarking technique. Results from the conducted tests show that the proposed technique able to generate a watermarked image that has no noticeable changes compared to its original image, with PSNR value more than 44 dB and SSIM value of almost 1, where the tamper detector can correctly detect and localize any tampering on the watermarked image. Furthermore, the proposed technique has shown to have a higher level of security on medical images, compared to DICOM standard and standard watermarking method. [ABSTRACT FROM AUTHOR]

Filter technique is supportive for reducing image noise. This paper presents a study on filtering medical images, i.e., CT-Scan, Chest X-ray and Panoramic X-ray collected from two of the most prominent public hospitals in Padang City, Indonesia. The aim of this study preserved to facilitate in diagnosing objects in x-ray medical images. This study used filter technique, i.e. Blur, Emboss, Gaussian, Laplacian, Roberts, Sharpen, or Sobel techniques as pre-processing step. The filter process performed before edge detection and edge clarification. MMG method used in this study to clarify the edge detection. Thus, this research showed the hesitation decline (confidence increase) of the diagnosis of objects contained in medical images. [ABSTRACT FROM AUTHOR]