2026-09-20T14:20:35Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1195722026-06-06T00:49:26Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Regina Barzilay.
Song, Hae Jin, S.M. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2018-12-11T20:40:38Z
2018-12-11T20:40:38Z
2018
2018
http://hdl.handle.net/1721.1/119572
1076344850
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 43-44).
This thesis presents a registration method for mammogram images with extended flexibility for manual inputs from medical specialists. The algorithm was developed as part of the Mammography project led by Professor. Regina Barzilay at MIT CSAIL. Given a sequence of mammogram images, the algorithm finds an optimal registration by considering both the global and local constraints as well as user-defined constraints such as manually selected matching points. This allows the registration process to be guided by both the algorithm itself and human experts. The second half of the thesis focuses on evaluating well-known optical flow and medical registration algorithms on mammogram images. It provides insights into how they perform when encountered by challenges and constraints that are unique in mammogram images.
by Hae Jin Song.
M.Eng.
44 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Non-rigid registration of mammogram images using large displacement optical flow with extended flexibility for manual interventions
Thesis
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<Abstract>This thesis presents a registration method for mammogram images with extended flexibility for manual inputs from medical specialists. The algorithm was developed as part of the Mammography project led by Professor. Regina Barzilay at MIT CSAIL. Given a sequence of mammogram images, the algorithm finds an optimal registration by considering both the global and local constraints as well as user-defined constraints such as manually selected matching points. This allows the registration process to be guided by both the algorithm itself and human experts. The second half of the thesis focuses on evaluating well-known optical flow and medical registration algorithms on mammogram images. It provides insights into how they perform when encountered by challenges and constraints that are unique in mammogram images.</Abstract>
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