DaEndoClusterMatching

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

Diploma/Master thesis: Endoscopic Cluster Matching

Endoscopic Cluster Matching
Thesis by:
Advisor: Nassir Navab
Supervision by: Selen Atasoy
Due date:

endo_clusters.png

Abstract

Diagnosis and treatment of the oesophageal cancer, the most rapidly increasing cancer in Western World, requires periodic examination of the tissue under endoscopic guidance together with systematic biopsies. During these examinations a flexible endoscope is inserted through the mouth of the patient into the oesophagus and biopsies (samples) are taken from suspicious regions of the tissue for pathologic investigation.

Recent developments in bio-photonics resulted in a new technology called probe-based Confocal Laser Endomicroscopy (pCLE) that enables real-time visualisation of cellular structures during the endoscopy without removing any tissue sample. A fibered confocal microprobe is introduced through the instrument channel of the endoscope to perform so called “optical biopsies”.

Although this procedure has several advantages over the conventional biopsy, it also introduces the new challenge of retargeting the optical biopsy locations in the follow-up examinations. Due to the lack of any markings such as a scar left on the tissue, re-targeting the optical biopsy locations becomes a challenge for endoscopic expert.

Recent work towards guiding the endoscopic expert in re-targeting optical biopsy sites presented very promising first step towards a complete framework for optical biopsy localisation. The aim of this project is to advance these techniques by an automatic cluster matching algorithm in order to develop a fully automatic system for optical biopsy re-targeting.

The project involves strong interaction with endoscopic experts from Klinikum Rechts der Isar.

If you are interested please send a brief CV to atasoy@in.tum.de.

Tasks

  • Literature study on cluster matching
  • Development of the cluster matching algorithm (prototype will be written in Matlab).
  • Validation of the method on real patient data.

Requirements

  • Strong knowledge of MATLAB (mandatory).
  • Good Math skills, in particular in manifold learning.
  • Interest in medical applications and multidisciplinary work.

Literature

  • S. Atasoy, D. Mateus, A. Meining, G. Z. Yang, N. Navab: Targeted Optical Biopsies for Surveillance Endoscopies, Medical Image Computing and Computer Assisted Intervention (MICCAI), Toronto, Canada, September 20-24 2011.
  • S. Atasoy, D. Mateus, J. Lallemand, A. Meining, G. Z. Yang, N. Navab: Endoscopic Video Manifolds, Medical Image Computing and Computer Assisted Intervention (MICCAI), Beijing, China, September 20-24 2010.
  • P. Mountney, S. Giannarou, D. Elson, G. Z. Yang: Optical Biopsy Mapping for Minimally Invasive Cancer Screening, Medical Image Computing and Computer Assisted Intervention (MICCAI), London, UK, September 20-24 2009.
  • Allain, B., Hu, M., Lovat, L., Cook, R., Ourselin, S., Hawkes, D.: Biopsy Site Re-localisation Based on the Computation of Epipolar Lines from Two Previous Endoscopic Images. In: Yang, G.Z., Hawkes, D., Rueckert, D., Noble, J., Taylor., C. (eds.) MICCAI 2009, Part I. LNCS, vol. 5761, pp. 491{498. Springer, Heidelberg (2009)
  • Allain, B., Hu, M., Lovat, L., Cook, R., Vercauteren, T., Ourselin, S., Hawkes, D.: A System for Biopsy Site Re-targeting with Uncertainty in Gastroenterology and Oropharyngeal Examinations. In: Jiang, T., Navab, N., Pluim, J., Viergever, M.A. (eds.) MICCAI 2010, Part II. LNCS, vol. 6362, pp. 514{521. Springer, Heidelberg (2010)
  • S. Atasoy, B. Glocker, S. Giannarou, D. Mateus, A. Meining, G. Z. Yang, N. Navab: Probabilistic Region Matching in Narrow-Band Endoscopy for Targeted Optical Biopsy, Medical Image Computing and Computer Assisted Intervention (MICCAI), London, UK, September 20-24 2009.


Students.ProjectForm
Title: Endoscopic Cluster Matching for Optical Biopsy Localisation
Abstract: Diagnosis and treatment of the oesophageal cancer, the most rapidly increasing cancer in Western World, requires periodic examination of the tissue under endoscopic guidance together with systematic biopsies. During these examinations a flexible endoscope is inserted through the mouth of the patient into the oesophagus and biopsies (samples) are taken from suspicious regions of the tissue for pathologic investigation. Recent developments in bio-photonics resulted in a new technology called probe-based Confocal Laser Endomicroscopy (pCLE) that enables real-time visualisation of cellular structures during the endoscopy without removing any tissue sample. A fibered confocal microprobe is introduced through the instrument channel of the endoscope to perform so called “optical biopsies”. Although this procedure has several advantages over the conventional biopsy, it also introduces the new challenge of retargeting the optical biopsy locations in the follow-up examinations. Due to the lack of any markings such as a scar left on the tissue, re-targeting the optical biopsy locations becomes a challenge for endoscopic expert. Recent work towards guiding the endoscopic expert in re-targeting optical biopsy sites presented very promising first step towards a complete framework for optical biopsy localisation. The aim of this project is to advance these techniques by an automatic cluster matching algorithm in order to develop a fully automatic system for optical biopsy re-targeting.
Student:  
Director:  
Supervisor: Selen Atasoy
Type: DA/MA/BA
Area:  
Status: finished
Start:  
Finish:  
Thesis (optional):  
Picture: endo_clusters.png


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