New approach to JPEG 2000 compliant region-of-interest coding

Author(s):  
Raphael Grosbois ◽  
Diego Santa-Cruz ◽  
Touradj Ebrahimi
Author(s):  
Sharath T. Chandrashekar ◽  
Gomata L. Varanasi

To provide efficient compression of medical images, identifying and extracting the region of interest from the entire image and coding the specific region to accuracy is important. This chapter introduces the basics of region of interest coding, an overview of the coding methods available and their main features for the benefit of learners and researchers. The special focus is on JPEG-2000-based algorithms.


2006 ◽  
Vol 21 (5) ◽  
pp. 359-377 ◽  
Author(s):  
Anthony Nguyen ◽  
Vinod Chandran ◽  
Sridha Sridharan

2002 ◽  
Vol 17 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Joel Askelöf ◽  
Mathias Larsson Carlander ◽  
Charilaos Christopoulos

Author(s):  
Neha Mehta ◽  
Svav Prasad ◽  
Leena Arya

Ultrasound imaging is one of the non-invasive imaging, that diagnoses the disease inside a human body and there are numerous ultrasonic devices being used frequently. Entropy as a well known statistical measure of uncertainty has a considerable impact on the medical images. A procedure for minimizing the entropy with respect to the region of interest is demonstrated. This new approach has shown the experiments using Extracted Region Of Interest Based Sharpened image, called as (EROIS) image based on Minimax entropy principle and various filters. In this turn, the approach also validates the versatility of the entropy concept. Experiments have been performed practically on the real-time ultrasound images collected from ultrasound centers and have shown a significant performance. The present approach has been validated with showing results over ultrasound images of the Human Gallbladder.


2018 ◽  
Vol 4 (1) ◽  
pp. 331-335
Author(s):  
David Schote ◽  
Tim Pfeiffer ◽  
Georg Rose

AbstractComputed tomography (CT) scans are frequently used intraoperatively, for example to control the positioning of implants during intervention. Often, to provide the required information, a full field of view is unnecessary. I nstead, the region-of-interest (ROI) imaging can be performed, allowing for substantial reduction in the applied X-ray dose. However, ROI imaging leads to data inconsistencies, caused by the truncation of the projections. This lack of information severely impairs the quality of the reconstructed images. This study presents a proof-of-concept for a new approach that combines the incomplete CT data with ultrasound data and time of flight measurements in order to restore some of the lacking information. The routine is evaluated in a simulation study using the original Shepp-Logan phantom in ROI cases with different degrees of truncation. Image quality is assessed by means of normalized root mean square error. The proposed method significantly reduces truncation artifacts in the reconstructions and achieves considerable radiation exposure reductions.


Sign in / Sign up

Export Citation Format

Share Document