Mr. Romulo Pinho Profile

Romulo Pinho

at Univ Antwerpen

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 12 March 2008 Paper

Seeing through the window: pre-fetching strategies for out-of-core image processing algorithms

R. Pinho, K. J. Batenburg, J. Sijbers

Proceedings Volume 6919, 69190D (2008) https://doi.org/10.1117/12.769423

KEYWORDS: Image processing, Medical imaging, Surgery, Computed tomography, Data processing, Operating systems, Visualization, Image storage, Algorithm development, Image visualization

Read Abstract +

Scientific data files have been increasing in size during the past decades. In the medical field, for instance, magnetic resonance imaging and computer aided tomography can yield image volumes of several gigabytes. While secondary storage (hard disks) increases in capacity and its cost per megabyte slumps over the years, primary memory (RAM) can still be a bottleneck in the processing of huge amounts of data. This represents a problem for image processing algorithms, which often need to keep in memory the original image and a copy of it to store the results. Operating systems optimize memory usage with memory paging and enhanced I/O operations. Although image processing algorithms usually work on neighbouring areas of a pixel, they follow pre-determined paths through the image and might not benefit from the memory paging strategies offered by the operating system, which are general purpose and unidimensional. Having the principles of locality and pre-determined traversal paths in mind, we developed an algorithm that uses multi-threaded pre-fetching of data to build a disk cache in memory. Using the concept of a window that slides over the data, we predict the next block of memory to be read according to the path followed by the algorithm and asynchronously pre-fetch such block before it is actually requested. While other out-of-core techniques reorganize the original file in order to optimize reading, we work directly on the original file. We demonstrate our approach in different applications, each with its own traversal strategy and sliding window structure.

Proceedings Article | 11 March 2008 Paper

Tracheal stent prediction using statistical deformable models of tubular shapes

R. Pinho, T. Huysmans, W. Vos, J. Sijbers

Proceedings Volume 6914, 69144O (2008) https://doi.org/10.1117/12.770237

KEYWORDS: Statistical analysis, Image segmentation, Computed tomography, Statistical modeling, Image processing, Endoscopes, Bronchoscopy, Data modeling, Silicon, Surgery

Read Abstract +

Tracheal stenosis is a narrowing of the trachea that impedes normal breathing. Tracheotomy is one solution, but subjects patients to intubation. An alternative technique employs tracheal stents, which are tubular structures that push the walls of the stenotic areas to their original location. They are implanted with endoscopes, therefore reducing the surgical risk to the patient. Stents can also be used in tracheal reconstruction to aid the recovery of reconstructed areas. Correct preoperative stent length and diameter specification is crucial to successful treatment, otherwise stents might not cover the stenotic area nor push the walls as required. The level of stenosis is usually measured from inside the trachea, either with endoscopes or with image processing techniques that, eg compute the distance from the centre line to the walls of the trachea. These methods are not suited for the prediction of stent sizes because they can not trivially estimate the healthy calibre of the trachea at the stenotic region. We propose an automatic method that enables the estimation of stent dimensions with statistical shape models of the trachea. An average trachea obtained from a training set of CT scans of healthy tracheas is placed in a CT image of a diseased person. The shape deforms according to the statistical model to match the walls of the trachea, except at stenotic areas. Since the deformed shape gives an estimation of the healthy trachea, it is possible to predict the size and diameter of the stent to be implanted in that specific subject.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years