Article: Using ROI with ISOM compression to medical image Journal: International Journal of Computational Vision and Robotics (IJCVR) 2016 Vol.6 No.1/2 pp.65 - 76 Abstract: The availability of images in different applications are augmented owing to the technological advancement. Hence, image compression has proved to be a valuable technique as one solution. This paper gives the review of compression techniques. Based on this, we recommended some general guidelines to choose the best compression algorithm for a medical image. In this method, the ROI is encoded separately using ISOM with high priority and high resolution and the back ground (BG) region which has a lower priority is separately encoded with a low resolution version of the ISOM. Finally, the two regions are merged together to get the reconstructed image. Our results show that the proposed method gives very good image quality for diagnosis without any degradable loss. The performance of the compression technique is evaluated using the parameters (MSE, and PSNR) and achieved better result compared to other existing methods. As a result, we strongly believe that using our method we can overcome the limitations in storage and transmission of medical images that are produced day by day. Inderscience Publishers - linking academia, business and industry through research

Title: Using ROI with ISOM compression to medical image

Authors: Imen Chaabouni; Wiem Fourati; Med Salim Bouhlel

Addresses: Science and Technologies of Image and Telecommunications High Institute of Biotechnology, Sfax, Tunisia ' Science and Technologies of Image and Telecommunications High Institute of Biotechnology, Sfax, Tunisia ' Science and Technologies of Image and Telecommunications High Institute of Biotechnology, Sfax, Tunisia

Abstract: The availability of images in different applications are augmented owing to the technological advancement. Hence, image compression has proved to be a valuable technique as one solution. This paper gives the review of compression techniques. Based on this, we recommended some general guidelines to choose the best compression algorithm for a medical image. In this method, the ROI is encoded separately using ISOM with high priority and high resolution and the back ground (BG) region which has a lower priority is separately encoded with a low resolution version of the ISOM. Finally, the two regions are merged together to get the reconstructed image. Our results show that the proposed method gives very good image quality for diagnosis without any degradable loss. The performance of the compression technique is evaluated using the parameters (MSE, and PSNR) and achieved better result compared to other existing methods. As a result, we strongly believe that using our method we can overcome the limitations in storage and transmission of medical images that are produced day by day.

Keywords: incremental self organising map; ISOM; JPEG; medical imaging; ultrasound images; ROI; region of interest; background; set partition in hierarchical tree; SPIHT; image compression; image quality; medical diagnosis.

DOI: 10.1504/IJCVR.2016.073759

International Journal of Computational Vision and Robotics, 2016 Vol.6 No.1/2, pp.65 - 76

Received: 02 Jan 2014
Accepted: 20 Sep 2014
Published online: 18 Dec 2015 *

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Title: Using ROI with ISOM compression to medical image

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