Home Publications Research Grants Inventions & Patents Awards Additional Research Activities Faculties & Institutions Research Areas

Automatic CAD-RADS Scoring using Deep Learning

Denzinger F, Wels M, Breininger K, Gülsün MA, Schöbinger M, Andre F, Buss SJ, Goerich J, Sühling M, Maier A (2020)

---

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2020

Publisher: Springer

City/Town: Cham

Conference Proceedings Title: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

Event location: Lima, Peru

ISBN: 978-3-030-59725-2

DOI: 10.1007/978-3-030-59725-2

Abstract

Coronary CT angiography (CCTA) has established its role as a non-invasive modality for the diagnosis of coronary artery disease (CAD). The CAD-Reporting and Data System (CAD-RADS) has been developed to standardize communication and aid in decision making based on CCTA findings. The CAD-RADS score is determined by manual assessment of all coronary vessels and the grading of lesions within the coronary artery tree. We propose a bottom-up approach for fully-automated prediction of this score using deep-learning operating on a segment-wise representation of the coronary arteries. The method relies solely on a prior fully-automated centerline extraction and segment labeling and predicts the segment-wise stenosis degree and the overall calcification grade as auxiliary tasks in a multi-task learning setup. We evaluate our approach on a data collection consisting of 2,867 patients. On the task of identifying patients with a CAD-RADS score indicating the need for further invasive investigation our approach reaches an area under curve (AUC) of 0.923 and an AUC of 0.914 for determining whether the patient suffers from CAD. This level of performance enables our approach to be used in a fully-automated screening setup or to assist diagnostic CCTA reading, especially due to its neural architecture design – which allows comprehensive predictions.

Authors with CRIS profile

Involved external institutions

How to cite

APA:

Denzinger, F., Wels, M., Breininger, K., Gülsün, M.A., Schöbinger, M., Andre, F.,... Maier, A. (2020). Automatic CAD-RADS Scoring using Deep Learning. In Martel AL, Abolmaesumi P, Stoyanov D, Mateus D, Zuluaga MA, Zhou SK, Racoceanu D, Joskowicz L (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. Lima, Peru: Cham: Springer.

MLA:

Denzinger, Felix, et al. "Automatic CAD-RADS Scoring using Deep Learning." Proceedings of the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, Lima, Peru Ed. Martel AL, Abolmaesumi P, Stoyanov D, Mateus D, Zuluaga MA, Zhou SK, Racoceanu D, Joskowicz L, Cham: Springer, 2020.

BibTeX: Download