A novel approach to tumor quantification and graphical model for image guided surgery

One of the problems confronting image guided surgery (IGS) is the time consumed at some stages of the procedure. This paper presents a methodological approach to calculating tumor volume by processing the MR image data records of patients and goes further to develop tumor model which could be use as...

Full description

Saved in:
Bibliographic Details
Main Authors: Aboaba, Abdulfattah A., Hameed, Shihab A., Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Harun, Rahmat H., Mohd Zain, Nurzaini Rose
Format: Article
Language:English
Published: Scottish Journal 2013
Subjects:
Online Access:http://irep.iium.edu.my/33586/1/Pages_from_SJASS_Vol.12_No.1-paper.pdf
http://irep.iium.edu.my/33586/
http://scottishjournal.co.uk/paper/SJASS_Vol.12_No.1.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:One of the problems confronting image guided surgery (IGS) is the time consumed at some stages of the procedure. This paper presents a methodological approach to calculating tumor volume by processing the MR image data records of patients and goes further to develop tumor model which could be use as a standard graphical model for tumor growth and decline for quick visual observation of patient’s tumor volume prior to IGS planning up to surgical intervention phase of the treatment. The work adopts a stepwise approach that starts with tumor area determination with the aid of iterative spatial sectoring (ISS) which enables tumor volume calculation using discrete integral function. This was followed by tumor area (TA) interpolation based on fast Fourier transform (FFT) and tumor averaging that engender tumor shape model in graphic form. This approach is novel and robust in that the model could also use non-IGS protocol images thereby enabling it reused for IGS planning and intervention. The resulting graphical model provide a quick way of comprehending tumor spread within the brain anatomy, and a fast method of approximating tumor volume during IGS planning, and intervention.