IdpProstateSegmentation

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Multimodal Prostate Segmentation (MRI and Ultrasound)

Project type: IDP
Advisor: Nassir Navab
Supervision by: Benjamin Frisch and Oliver Zettinig

Abstract

In the clinical routine, systematic untargeted needle biopsies are currently considered gold standard to identify malignant lesions in the prostate. Our group at CAMP has a focus on developing new applications for prostate cancer diagnosis, improving the clinical procedures and allowing a more targeted approach for diagnosis and treatment planning. To that end, data from different imaging modalities (CT, MRI, Ultrasound, SPECT, PET) have to be combined and collectively taken into account. A reliable segmentation of the prostate and the surrounding tissue in each of these images acts as the starting point for a variety of further processing.

The objective of this IDP is to develop and implement advanced segmentation algorithms in order to allow automatic segmentation of the prostate gland in MR and US volumetric images. Your task would be to familiarize yourself with the challenges posed by MR and especially trans-rectal ultrasound (TRUS) imaging, as well as state-of-the-art algorithms suited to tackle a detailed segmentation. You will then implement the algorithms in CAMPVis, the visualization framework developed at our chair, and iteratively evaluate the algorithms' performance with an extensive available dataset.

We require good knowledge of C++ and the ability to work independently, some experience with image processing is an advantage.

If you are interested please send your up-to-date CV to .

campvis_mr_trus.jpg
Fig. 1: Example MR and TRUS images, in which the prostate have to be segmented correspondingly.

ProjectForm
Title: Multimodal Prostate Segmentation
Abstract: The objective of this IDP is to develop and implement advanced segmentation algorithms in order to allow automatic segmentation of the prostate gland in MR and US volumetric images. Your task would be to familiarize yourself with the challenges posed by MR and especially trans-rectal ultrasound (TRUS) imaging, as well as state-of-the-art algorithms suited to tackle a detailed segmentation. You will then implement the algorithms in CAMPVis, the visualization framework developed at our chair, and iteratively evaluate the algorithms' performance with an extensive available dataset.
Student:  
Director: Nassir Navab
Supervisor: Benjamin Frisch and Oliver Zettinig
Type: IDP
Area: Segmentation, Medical Imaging
Status: finished
Start:  
Finish:  
Thesis (optional):  
Picture:  


Edit | Attach | Refresh | Diffs | More | Revision r1.4 - 06 Mar 2015 - 14:54 - OliverZettinig