Diploma thesis (DA): Automated Segmentation of Sentinel Lymph Nodes from Freehand SPECT Images of Breast Cancer Patients

Thesis by: Asli Okur
Advisor: Prof. Nassir Navab
Supervision by: Tobias Lasser and Thomas Wendler
Submission date: September 15, 2010

Abstract

Freehand SPECT is a 3D imaging modality for emission tomography based on data acquisition with a tracked gamma probe that is moved around a localized region in freehand fashion, in contrast to conventional SPECT systems with fixed gamma cameras. After validation in pre-operative studies, first intra-operative studies have commenced.

In this thesis an automatic 3D segmentation algorithm for Freehand SPECT reconstructions is developed. The segmented regions are then investigated using an iterative leveling algorithm to find topology changes in various threshold intervals. These algorithms are used to analyze real patient data to find relations between regions using information about size, activity and distances. For an easier evaluation, a graphical user interface is designed and further improvements are applied.

A reproducibility test is done using 33 acquisitions of the same phantom to validate the segmentation and to evaluate the distance measurement between regions. Furthermore, a patient data analysis is done with a set of 25 acquisitions. The deficiencies of the automatic approach are identified and further improvement options are suggested so that the program can estimate optimal threshold values for visualization (semi-) automatically.