Mr. Alexander Muehlberg Profile

Alexander Muehlberg

at Siemens Healthineers

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 13 March 2019 Paper

General purpose radiomics for multi-modal clinical research

Michael Wels, Félix Lades, Alexander Muehlberg, Michael Suehling

Proceedings Volume 10950, 1095046 (2019) https://doi.org/10.1117/12.2511856

KEYWORDS: Statistical analysis, Image segmentation, Data modeling, Clinical research, Computed tomography, Medical imaging, Lung cancer, Feature selection, 3D image processing, Machine learning

Read Abstract +

In this paper we present an integrated software solution^∗ targeting clinical researchers for discovering relevant radiomic biomarkers covering the entire value chain of clinical radiomics research. Its intention is to make this kind of research possible even for less experienced scientists. The solution provides means to create, collect, manage, and statistically analyze patient cohorts consisting of potentially multimodal 3D medical imaging data, associated volume of interest annotations, and radiomic features. Volumes of interest can be created by an extensive set of semi-automatic segmentation tools. Radiomic feature computation relies on the de facto standard library PyRadiomics and ensures comparability and reproducibility of carried out studies. Tabular cohort studies containing the radiomics of the volumes of interest can be managed directly within the software solution. The integrated statistical analysis capabilities introduce an additional layer of abstraction allowing non-experts to benefit from radiomics research as well. There are ready-to-use methods for clustering, uni- and multivariate statistics, and machine learning to be applied to the collected cohorts. They are validated in two case studies: for one thing, on a subset of the publicly available NSCLC-Radiomics data collection containing pretreatment CT scans of 317 non-small cell lung cancer (NSCLC) patients and for another, on the Lung Image Database Consortium imaging study with diagnostic and lung cancer screening CT scans including 2,753 distinct lesions from 870 patients. Integrated software solutions with optimized workflows like the one presented and further developments thereof may play an important role in making precision medicine come to life in clinical environments.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

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

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years