MaMTL

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

Gradient Surgery for Multitask Longitudinal CT Analysis

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

Abstract

Longitudinal changes of pathology in CT images is an important indicator for analyzing patients from COVID19. In the clinical setting, clinicians read longitudinal images to get various information such as disease progression, needs for ICU admission, the severity of the disease. They are important to increase the survival rate. However, reading longitudinal 3D CT scans takes a long time which might decrease the efficiency of the clinician's performance. In this project, we will explore a method to automatically analyze longitudinal CT scans to help the radiologist's reading. In particular, we will explore a multitask learning method to fully exploit the relation between different tasks and adaptively balancing the gradients from different objective functions (i.e. Gradient surgery).

Requirements:

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

Location:

  • Garching

ProjectForm
Title: Gradient Surgery for Multitask Longitudinal CT Analysis
Abstract: Longitudinal changes of pathology in CT images is an important indicator for analyzing patients from COVID19. In the clinical setting, clinicians read longitudinal images to get various information such as disease progression, needs for ICU admission, the severity of the disease. They are important to increase the survival rate. However, reading longitudinal 3D CT scans takes a long time which might decrease the efficiency of the clinician's performance. In this project, we will explore a method to automatically analyze longitudinal CT scans to help the radiologist's reading. In particular, we will explore a multitask learning method to fully exploit the relation between different tasks and adaptively balancing the gradients from different objective functions (i.e. Gradient surgery).
Student:  
Director: Prof. Dr. Nassir Navab
Supervisor: Dr. Seong Tae Kim
Type: Master Thesis
Area: Machine Learning, Medical Imaging
Status: running
Start:  
Finish:  
Thesis (optional):  
Picture:  


Edit | Attach | Refresh | Diffs | More | Revision r1.1 - 23 Sep 2020 - 22:29 - SeongTaeKim