MaLongicovid

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

Longitudinal CT analysis for monitoring COVID

Supervision: Prof. Dr. Nassir Navab, Dr. Seong Tae Kim, Tobias Czempiel

Abstract

Longitudinal changes of pathology in CT images is an important indicator for analyzing patients from COVID19. To accurately analyze changes of pathologies, consistent segmentation across multiple time-points is required. Existing methods often involve independent registration and segmentation algorithms. In this project, we will explore hybrid deep neural networks that integrate segmentation and registration into a single procedure. Furthermore, we will explore an effective way to predict important clinical information such as disease progression, the probability of death (from segmented pathologies, and image features of longitudinal CT scans).

Requirements:

  • Good understanding of statistics and machine learning methods.
  • Very good programming skills in Python & TensorFlow? / PyTorch?

Location:

  • Garching

If you are interested in this project, please feel free to contact Dr. SeongTae? (seongtae.kim@tum.de)

ProjectForm
Title: Longitudinal CT analysis for monitoring COVID
Abstract: Longitudinal changes of pathology in CT images is an important indicator for analyzing patients from COVID19. To accurately analyze changes of pathologies, consistent segmentation across multiple time-points is required. Existing methods often involve independent registration and segmentation algorithms. In this project, we will explore hybrid deep neural networks that integrate segmentation and registration into a single procedure. Furthermore, we will explore an effective way to predict important clinical information such as disease progression, the probability of death (from segmented pathologies, and image features of longitudinal CT scans).
Student:  
Director: Prof. Dr. Nassir Navab
Supervisor: Dr. Seong Tae Kim, Tobias Czempiel
Type: Master Thesis
Area: Machine Learning, Medical Imaging
Status: open
Start:  
Finish:  
Thesis (optional):  
Picture:  


Edit | Attach | Refresh | Diffs | More | Revision r1.1 - 06 Jul 2020 - 22:48 - SeongTaeKim