Fully automated longitudinal tracking and in-depth analysis of the entire tumor burden: unlocking the complexity

Sven Kuckertz; Jan Klein; Christiane Engel; Benjamin Geisler; Stefan Kraß; Stefan Heldmann

doi:10.1117/12.2613080

4 April 2022 Fully automated longitudinal tracking and in-depth analysis of the entire tumor burden: unlocking the complexity

Sven Kuckertz, Jan Klein, Christiane Engel, Benjamin Geisler, Stefan Kraß, Stefan Heldmann

Author Affiliations +

Proceedings Volume 12033, Medical Imaging 2022: Computer-Aided Diagnosis; 120331Q (2022) https://doi.org/10.1117/12.2613080
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

We present a novel approach for handling complex information of lesion segmentation in CT follow-up studies. The backbone of our approach is the computation of a longitudinal tumor tree. We perform deep learning based segmentation of all lesions for each time point in CT follow-up studies. Subsequently, follow-up images are registered to establish correspondence between the studies and trace tumors among time points, yielding tree-like relations. The tumor tree encodes the complexity of the individual disease progression. In addition, we present novel descriptive statistics and tools for correlating tumor volumes and RECIST diameters to analyze significance of various markers.

Citation Download Citation

Sven Kuckertz, Jan Klein, Christiane Engel, Benjamin Geisler, Stefan Kraß, and Stefan Heldmann "Fully automated longitudinal tracking and in-depth analysis of the entire tumor burden: unlocking the complexity", Proc. SPIE 12033, Medical Imaging 2022: Computer-Aided Diagnosis, 120331Q (4 April 2022); https://doi.org/10.1117/12.2613080

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available