DocumentCode
172601
Title
A Segmentation Method for Bone Marrow Cavity Imaging Using Graph Cuts
Author
Mashita, Tomohiro ; Usam, Jun ; Shigeta, Hironori ; Kuroda, Yoshihiro ; Kikuta, Junichi ; Senoo, Shigeto ; Ishi, Masaru ; Matsuda, Hidemitsu ; Takemura, Hiroshi
Author_Institution
Cybermedia Center, Osaka Univ., Suita, Japan
fYear
2014
fDate
24-24 Aug. 2014
Firstpage
20
Lastpage
23
Abstract
The improvement of bioimaging technologies enables the observation of cellular dynamics invivo. Some new bioimaging technologies are expected to contribute to the discovery of new drugs and mechanisms of disease. To improve the contributions of bioimaging, it is required to extract a particular region or to detect a particular cell´s motion within bioimages. Moreover, automatic extraction and detection with image processing is also required because the accurate and uniformed processing of a massive number of images manually is unrealistic. To help automate this process, we introduce a bone marrow cavity segmentation method for two-photon excitation microscopy images. Specialists of cellular dynamics define regions of bone marrow cavity by considering several criteria, including characteristics of intensity and blood flow. We take those criteria into our method as the energy function of graph cuts. Results of evaluations and comparison with normal graph cuts show that our proposed method that does not use hard constraints achieved a performance better than normal graph cuts with hard constraints.
Keywords
bone; cellular biophysics; haemodynamics; haemorheology; image segmentation; medical image processing; microscopy; bioimaging technologies; blood flow; bone marrow cavity imaging; bone marrow cavity segmentation method; cellular dynamics; graph cuts energy function; intensity characteristics; normal graph cuts; two-photon excitation microscopy images; Blood; Bones; Cavity resonators; Educational institutions; Image segmentation; Microscopy; Bone Marrow Cavity Image; Graph Cuts;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition Techniques for Indirect Immunofluorescence Images (I3A), 2014 1st Workshop on
Conference_Location
Stockholm
Type
conf
DOI
10.1109/I3A.2014.21
Filename
6973541
Link To Document