Contributions to Computed Tomography Image Coding for JPEG2000

Abstract

Nowadays, thanks to the advances in medical science, there exist many different medical imaging_x000D_ techniques aimed at seeking to reveal, diagnose, or examine a disease. Many of these techniques_x000D_ produce very large amounts of data, especially from Computed Tomography (CT), Magnetic Res-_x000D_ onance Imaging (MRI) and Positron Emission Tomography (PET) modalities. To manage these_x000D_ data, medical centers use PACS and the DICOM standard to store, retrieve, distribute, and display_x000D_ medical images. As a result of the high cost of storage and transmission of medical digital images,_x000D_ data compression plays a key role._x000D_ JPEG2000 is the state-of-the-art of image compression for the storage and transmission of med-_x000D_ ical images. It is the latest coding system included in DICOM and it provides some interesting_x000D_ capabilities for medical image coding. JPEG2000 enables the use of use of windows of interest,_x000D_ access different resolutions sizes of the image or decode an specific region of the image._x000D_ _x000D_ This thesis deals with three different problems detected in CT image coding. The first coding_x000D_ problem is the noise that CT have. These noise is produced by the use of low radiation dose during the_x000D_ scan and it produces a low quality images and penalizes the coding performance. The use of different_x000D_ noise filters, enhance the quality and also increase the coding performance. The second question_x000D_ addressed in this dissertation is the use of multi-component transforms in Computed Tomography_x000D_ image coding. Depending on the correlation among the slices of a Computed Tomography, the_x000D_ coding performance of these transforms can vary even decrease with respect to JPEG2000. Finally,_x000D_ the last contribution deals with the diagnostically lossless coding paradigm, and it is proposed a_x000D_ new segmentation method. Through the use of segmentation methods to detect the biological area_x000D_ and to discard the non-biological area, JPEG2000 can achieve improvements of more than 2bpp.

Date of Award	13 Jan 2014
Original language	Undefined/Unknown
Supervisor	Joan Bartrina Rapesta (Director)