Effective and Accelerated Informative Frame Filtering in Colonoscopy Videos Using Graphic Processing Units

PDF Version Also Available for Download.

Description

Colonoscopy is an endoscopic technique that allows a physician to inspect the mucosa of the human colon. Previous methods and software solutions to detect informative frames in a colonoscopy video (a process called informative frame filtering or IFF) have been hugely ineffective in (1) covering the proper definition of an informative frame in the broadest sense and (2) striking an optimal balance between accuracy and speed of classification in both real-time and non real-time medical procedures. In my thesis, I propose a more effective method and faster software solutions for IFF which is more effective due to the introduction of ... continued below

Physical Description

vii, 55 p. : ill.

Creation Information

Karri, Venkata Praveen August 2010.

Context

This thesis is part of the collection entitled: UNT Theses and Dissertations and was provided by UNT Libraries to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 395 times , with 6 in the last month . More information about this thesis can be viewed below.

Who

People and organizations associated with either the creation of this thesis or its content.

Chair

Committee Members

Publisher

Rights Holder

For guidance see Citations, Rights, Re-Use.

  • Karri, Venkata Praveen

Provided By

UNT Libraries

With locations on the Denton campus of the University of North Texas and one in Dallas, UNT Libraries serves the school and the community by providing access to physical and online collections; The Portal to Texas History and UNT Digital Libraries; academic research, and much, much more.

Contact Us

What

Descriptive information to help identify this thesis. Follow the links below to find similar items on the Digital Library.

Description

Colonoscopy is an endoscopic technique that allows a physician to inspect the mucosa of the human colon. Previous methods and software solutions to detect informative frames in a colonoscopy video (a process called informative frame filtering or IFF) have been hugely ineffective in (1) covering the proper definition of an informative frame in the broadest sense and (2) striking an optimal balance between accuracy and speed of classification in both real-time and non real-time medical procedures. In my thesis, I propose a more effective method and faster software solutions for IFF which is more effective due to the introduction of a heuristic algorithm (derived from experimental analysis of typical colon features) for classification. It contributed to a 5-10% boost in various performance metrics for IFF. The software modules are faster due to the incorporation of sophisticated parallel-processing oriented coding techniques on modern microprocessors. Two IFF modules were created, one for post-procedure and the other for real-time. Code optimizations through NVIDIA CUDA for GPU processing and/or CPU multi-threading concepts embedded in two significant microprocessor design philosophies (multi-core design and many-core design) resulted a 5-fold acceleration for the post-procedure module and a 40-fold acceleration for the real-time module. Some innovative software modules, which are still in testing phase, have been recently created to exploit the power of multiple GPUs together.

Physical Description

vii, 55 p. : ill.

Language

Identifier

Unique identifying numbers for this thesis in the Digital Library or other systems.

Collections

This thesis is part of the following collection of related materials.

UNT Theses and Dissertations

Theses and dissertations represent a wealth of scholarly and artistic content created by masters and doctoral students in the degree-seeking process. Some ETDs in this collection are restricted to use by the UNT community.

What responsibilities do I have when using this thesis?

When

Dates and time periods associated with this thesis.

Creation Date

  • August 2010

Added to The UNT Digital Library

  • March 30, 2011, 9:15 p.m.

Description Last Updated

  • June 20, 2011, 3:42 p.m.

Usage Statistics

When was this thesis last used?

Yesterday: 0
Past 30 days: 6
Total Uses: 395

Interact With This Thesis

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Karri, Venkata Praveen. Effective and Accelerated Informative Frame Filtering in Colonoscopy Videos Using Graphic Processing Units, thesis, August 2010; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc31536/: accessed September 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .