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Thesis Defence of Doctoral in Information Technology: Rifki Kosasih and Dewi Putrie Lestari

On October, 28th 2015, Doctoral Program Gunadarma University conducted doctoral thesis defence in Information Technology at Auditorium of Gunadarma University, Campus D, Jl. Margonda Raya, Pondok Cina, Depok.

As the first candidat, Rifki Kosasih presented his thesis dissertation with title “The Development of Extraction and 3D Reconstruction Algorithm in The Lumen Contained Thrombus in Patients with Abdominal Aortic Aneurysm and Visualization of Blood Flow”. The advisors committee are Profesor Doktor Sarifuddin Madenda as a Promotor and Profesor Doktor BEF da Silva also Doktor Lussiana ETP as Co-Promotor, and as external examiner is Dr. Ir. Agus Buono, M.Si, M.Kom.

This research proposes the analysis of the blood flow in lumen area of aorta. Abdominal aortic aneurysm (AAA) is a disease caused by dilation of the aortic wall. To detect AAA is required a digital examination tools such as MRI (Magnetic Resonance Imaging) which can acquire a digital image of the aorta in the form of images T1 and T2 relaxation. An indicator used to determine the existence of AAA in the aorta is by measure the diameter of the aorta. However, this indicator has not been able to predict the occurrence of rupture or rupture of the aorta. To predict the rupture required further analysis is to determine volume and direction of blood flow in the aorta.

From the results of research, obtained that the alignment of the image by using Laplacian eigenmap method results most optimal position (100% exactly the same). This result also gives the results of the extraction area in the aortic lumen more optimal.

The second candidate is Dewi Putrie Lestari with Profesor Doktor Sarifuddin Madenda as The Promotor and Doktor Eri Prasetyo Wibowo also Doktor Ernastuti, S.Si, M.Kom as Co-Promotor, and Doktor Setiawan Hadi, M.Sc.CS as external examiner.

Breast cancer is one of the leading causes of death among women both in developed countries and in developing countries. One of the medical diagnosis tools to detect breast cancer is ultrasound. Reading of ultrasound images in detection breast cancer requires experienced radiologists. The difference understanding the results of the analysis image among the radiologists can cause for differing diagnosis (CAD) that can be able to detect and grouping breast tumors precisely. The precision of grouping breast tumors is highly dependent on the accuracy of segmentation results of tutor area, which is the first step of a CAD system.

This research aims to build CAD system of breast ultrasound images by proposing two things: the development of breast tumor area extraction method and new algorithm for feature extraction the shape of a tutor.

From the result can be concluded, the results of this method proved to be quite accurate based on Jaccard similarity measurement method with the average value of similarity of 90% and the level of dissimilarity based on Hausdorff Distance method with the average value of dissimilarity much as 8 pixels.

The  Senate Committee of Gunadarma University determine these two candidates were graduated with Cumlaude. Doctor Rifki Kosasih and Dewi Putrie Lestari are 84th and 85th Doctor of Information Technology in Gunadarma University.

Expected from the results of these study can contribute and benefit theoretically and technology development.