Dissertation defense - Mahdieh Farzin Asanjan

Graduate School of Informatics /Health Informatics

In partial fulfillment of the requirements for the degree of Master of Science Mahdieh Farzin Asanjan will defend his thesis.


Date: 16th June 2017

Time: 10:30 AM

Place: A-108

Thesis Abstract : Semi-automatic segmentation of mitochondria Segmentation is an integral part of image processing. Contrary to many technical applications the design of fully automated segmentation routines is extremely challenging in the medical context because of the large biological variation. Even if automatic routines do work in normal subjects, they typically fail in pathologic cases, which are often more interesting from a clinical point of view. Segmentation of mitochondria in medical images is essential for studying mitochondrial morphology and computer aided analysis and diagnosis. Since using an automatic segmentation method may leads to the least flexibility and also using the manual methods needs a considerable amount of human effort, automatic detection and segmentation of mitochondria with user interaction is necessary in order to facilitate the analysis of large 3D data sets and user interaction introduces a subjective element to image processing and analysis. So segmentation methods using human interaction to initialize the algorithms can be more helpful. In new method I am trying to make possible to operator interaction although it may be used in a minority of cases, only. And this will help to reduce the failure rates. Two principle modes of user interaction can be distinguished. In the first mode the user interactively selects a region or volume of interest (ROI or VOI) in which subsequently an automated operation is performed. A typical well-known example is the selection of a seed point to start a region growing process. In contrast, the second mode is iterative and requires extended user interaction, for example, an interactive change of a contour.