MIDL 2021

International Conference on
Medical Imaging with Deep Learning
5. bis 7. Juli 2021

Mammo3D – Automatic Detection and Visualization of Corresponding Structures and Lesions in 2D/3D Image Data of the Female Breast for Multimodal Breast Cancer Diagnosis

Two-dimensional digital mammography is the major imaging modality for breast cancer diagnostic and early detection. To improve diagnostics additional modalities such as magnetic resonance imaging and digital breast tomosynthesis can be used or additional mammograms acquired with a different projection angle (CC or MLO) are generated. A combined analysis of the different medical image data of the same patient would be preferable to facilitate diagnostics and treatments.

The main objective of this project is the automatic detection and visualization of corresponding structures in the acquired image data and the processing of these structures to establish a basis for multimodal breast cancer diagnosis.
The focus of our work lies in the development and evaluation of methods for multidimensional and multimodal image registration and correspondence analysis. The development of deformation models of the female breast poses a further challenge, as the breast is exposed to different compressions and deformations during the acquisition of the different image data.

The project is realized in collaboration with the company IMAGE Information Systems Europe Ltd. and is funded by the German Federal Ministry of Economy and Technolgy BMWi.

Fig. 1: Aim of the project is the detection of corresponding structures in mammograms, tomosynthesis and MRI data.

Selected Publications:

  1. Krüger J, Ehrhardt J, Bischof A, Handels H
    Simulation of Mammographic Breast Compression in 3D MR images using ICP-based B-Spline Deformation for Multimodality Breast Cancer Diagnosis.
    International Journal of Computer Assisted Radiology and Surgery. In Press
  2. Krüger J, Ehrhardt J, Bischof A, Handels H
    Breast Compression Simulation using ICP-based B-Spline Deformation for Correspondence Analysis in Mammography and MRI Datasets.
    Image Processing, SPIE Medical Imaging 2013. :8669-48,1D1-1D8. 2013
  3. Krüger J, Ehrhardt J, Bischof A, Handels H
    Evaluation of a B-Spline-based Breast Compression Simulation for Correspondence Analysis between MRI and Mammographic Image Data.
    Workshop on Breast Image Analysis - In conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2013) 17-24, 2013
  4. Ehrhardt J., Krüger J., Bischof A., Handels H.
    Automatic Correspondence Detection in Mammogram and Breast Tomosynthesis Images.
    Image Processing, SPIE Medical Imaging 2012. 8314:831421-1-831421-8. 2012
  5. Krüger J., Ehrhardt J., Bischof A., Barkhausen J., Handels H.
    Automatische Bestimmung von 2D/3D-Korrespondenzen in Mammographien und Tomosynthese-Bilddaten.
    Bildverarbeitung für die Medizin 2012, Informatik aktuell, 99-104, 2012

Project Team:

M. Sc. Matthias Wilms
M.Sc. Julia Krüger
Dr. Jan Ehrhardt
Prof. Dr. Heinz Handels

Cooperation Partners:

Arpad Bischof und Prof. Dr. med. Jörg Barkhausen
Clinic for Radiology and Nuclear Medicine
University Medical Center Schleswig-Holstein, Campus Lübeck

Andreas Berger
IMAGE Information Systems Europe Ltd.


Created at February 20, 2012 - 2:13pm by Kulbe. Last modified at June 30, 2014 - 11:45am.


Program of Study

Study Medical Informatics
at the University of Lübeck

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Susanne Petersen

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