ProjectStenosisClassification

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

Non Invasive Histology of Atherosclerotic Plaque

Non Invasive Histology of Atherosclerotic Plaque

In medical collaboration with:
Dr. Holger Poppert, Dr. Lorena Esposito, Prof. Dr. Eckstein (Klinikum rechts der Isar)

Scientific Director: Prof. Dr. Nassir Navab

Contact Person(s): Olivier Pauly

Keywords: Segmentation, Machine Learning for Medical Applications, IFL

Abstract

Stroke is the third leading cause of death in Germany. It is a neurology injury, whereby the oxygen supply to parts of the brain gets cut off. About 80% of these strokes are due to ischemia, i.e. an occlusion of a blood vessel leading to an interrupted blood flow. Stenosis inside the carotid artery imaged using four different MR weightings Special setting in this project is the arteria carotis. Plaque is most likely to develop at the branching of the arteria carotis communis into the arteria carotis interna (leading to the brain) and the arteria carotis externa. This can lead to an abnormal narrowing, called a stenosis. According to the American Heart Association these plaques can be divided into different types, based on their consistency and structure. Until now the decision about a surgery was only based on the degree of the stenosis and not on the type of plaque causing it. This is a faulty approach since there is a plaque type (Type IV) which constitutes a relevant clinical danger, although it does not necessary come along with a stenosis. Unlike most other image modalities MR images do not only give information about the degree of the stenosis, but also about the consistency of the plaque. Using different weighted MR images it is possible to correctly classify plaque into the types defined by the AHA. The main goal of this project is to create a classification tool based on T1, T2, Proton Density and 'Time of flight' weighted images. To achieve this goal the arteria carotis and the plaque have to be segmented from the images. Furthermore various features of the plaque have to be extracted in order to get information needed for the classification.

Pictures

Figure 1: MR T1, T2, PD and TOF images of the Carotid artery
Figure 2: MR T1 3D volume of the Carotid artery
Figure 3: MR T1 3D volume of the Carotid artery
Figure 4: NIHAP Tool Version 1.0

Team

Contact Person(s)

Olivier Pauly
Dr. Olivier Pauly

Working Group

Ali Bigdelou
Dr. Ali Bigdelou
Holger Poppert
Dr. med. Holger Poppert
Lorena Esposito
Dr. med. Lorena Esposito
Nassir Navab
Prof. Dr. Nassir Navab
Olivier Pauly
Dr. Olivier Pauly
Vladimir Golkov
Vladimir Golkov

Alumni

Andreas Keil
Dr. Andreas Keil
Anna Medvedeva
M.Sc. Anna Medvedeva
Mehmet Yigitsoy
Dr. Mehmet Yigitsoy
Nicolas Padoy
Dr. Nicolas Padoy

Location



Technische Universität München
Institut für Informatik / I16
Boltzmannstr. 3
85748 Garching bei München

Tel.: +49 89 289-17058
Fax: +49 89 289-17059
Visit our lab at Garching.



Klinikum rechts der Isar
der Technischen Universitüt München
Ismaninger Str. 22
81675 München

IFL Lab - Room: 01.3a-c
Tel.: +49 89 4140-6457
Fax: +49 89 4140-6458
Visit our lab at Klinikum rechts der Isar.



internal project page

Please contact Olivier Pauly for available student projects within this research project.

Edit | Attach | Refresh | Diffs | More | Revision r1.1 - 13 Dec 2007 - 17:28 - AndreasKeil

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