International Conference on Computer and Communication Engineering (ICCCE 2012), 3-5 July 2012, Kuala Lumpur, Malaysia 978-1-4673-0479-5/12/$31.00 ©2012 IEEE Evolution of Brain Tumor Growth Model: A Back-in-Time Approach Abdulfattah A. Aboaba 1, 2 , Shihab A. Hameed 1 , Othman O. Khalifa 1 , Aisha H. Abdalla 1 , Rahmat H. Harun 3 , Norzaini Rose Mohd Zain 4 1 Department of Electrical & Computer Engineering, International Islamic University Malaysia 2 Computer Engineering Department, University of Maiduguri Nigeria 3 Klinik Pakar Neurosurgeri, Hospital Queen Elizabeth, Kota Kinabalu, Sabah Malaysia 4 Radiology Department, Hospital Kuala Lumpur Malaysia abdulfattahaa@gmail.com. , shihab@iiu.edu.my , khalifa@iiu.edu.my , aisha@iiu.edu.my , rahmat865@yahoo.com , norzainirose@yahoo.co.uk Abstract—One of the crucial stages in Image Guided Surgery (IGS) protocol is the IGS planning stage, the major requirements at that stage are to determine tumor extent and size by reconstructing tumor slices, and to determine the best way to approach affected site. The surgeon is clinically responsible to do these with the aid of IGS software that is fashioned in line with the surgeon training. It has been observed that lots of time used at that stage could be saved if a good model that will accurately estimate tumor growth from few slices could be developed to assist at that stage. This paper presents a tumor growth modeling approach based on step response of electrical energy devices, and its application to tumor estimation using non-IGS protocol image slices to produce tumor area estimation that is comparable for image reconstruction purposes with tumor area found on the thin slice IGS protocol images, thereby eliminating the need for time consuming IGS protocol imaging. Index Terms – IGS Planning, tumor extent, step response, tumor estimation, IGS software, saves time. I.INTRODUCTION The fact that the time used at various stages of IGS protocol is worrisome has been discussed in [1],[2],[3]. Also, the inaccuracies associated with the clinical method of brain segmentation and quantification was featured in [2],[3],[4]. Again, a futuristic approach in which robots would be deployed into neuro-surgical intervention where accurate segmentation and precise brain tumor volume would be highly needed was foresaw by [5], and [6]. All these call for a better and more efficient, effective, smart, and automated system especially for brain tumor quantification. In anatomy, Tumor/ cancer/ neoplasm/ lump are considered as unusual growth, if unchecked; they spread within the body anatomy, and are responsible for a range of diseases. Moreover, tumor spread also depends on the adjacent cell types that are neighboring the tumorous cell. If the neighboring cells are of the same parent cell with the tumor infected cell, tumor spread would be faster otherwise its spread is slower. Tumors are categorized based on their ability to spread or lack of it. The present discuss is focused on already matured or troublesome tumor that has been diagnosed for treatment/ removal. Tumor estimation could be used for varied types of treatment but the direction of this paper is surgical intervention by human surgeon or a more optimistic automated robotic surgeon performing neuro- surgical operation. Many researchers have equally recognized the need to fashion a way out of the clinical method of tumor quantification among whom are [1] who proclaimed the use of images to identify tumor extent, and in addition to that, many classical works such as [7] have proposed a method called ‘partial volume model’ based on voxel information, and [8] using fusion technique, which are aimed at determining tumor extent including several biopsies methods, [9] who reported lots of fractal analysis methods of identifying tumor boundary, and authors like [10][11][12][13][14], and [15] have reported worthy segmentation methods whose eventual target is determination of tumor coverage. In clinical neuro-surgery, a patient undergoes IGS protocol imaging once his case has been decided as needing surgical intervention. The IGS protocol imaging is usually the last (at best the second) of imaging the patient would undergo before surgical intervention meaning he must have done some (at least one) non-IGS imaging for use by the physician prior to final determination for surgical intervention. Many patients are uncomfortable when asked to go into the MRI machine which is the best for soft tissue imaging like brain. Apart from this psychological trauma on the part of the patient, there is also cost consideration he has to come to terms with. Added to these is the length of time he needs to stay inside the machine for IGS protocol imaging which is far longer that imaging for non-IGS purposes. This is partly because for IGS protocol imaging thinner slice thickness is required owing to the slice reconstruction that would be done at the IGS planning stage before surgical intervention. It is the requirement for another round of imaging for purpose of IGS that this work is aimed at abolishing in such a way that using the tumor model, and instantaneous tumor are equation devised and proposed in the work, a non-IGS protocol image would be found useful for reconstruction at the IGS planning. The approach we employed in achieving tumor model and instantaneous tumor area equation (Tum(h) is to 982