Automated anatomical labeling of abdominal arteries and hepatic portal system extracted from abdominal CT volumes

Medical Image Analysis

Volumn 20, Issue 1, 2015, Pages 152-161

  Matsuzaki, Tetsuro ^a   Oda, Masahiro ^a   Kitasaka, Takayuki ^b   Hayashi, Yuichiro ^a   Misawa, Kazunari ^c   Mori, Kensaku ^a  

^a NAGOYA UNIVERSITY   (Japan)

^b AICHI INSTITUTE OF TECHNOLOGY   (Japan)

^c AICHI CANCER CENTER HOSPITAL   (Japan)

Author keywords

Analysis of blood vessel structures; Blood vessel; CT volume; Recognition of anatomical names

Indexed keywords

ARTIFICIAL INTELLIGENCE; FORESTRY; LEARNING SYSTEMS; TREES (MATHEMATICS);

ABDOMINAL SURGERY; ANATOMICAL LABELING; CT VOLUME; LIKELIHOOD FUNCTIONS; MACHINE LEARNING TECHNIQUES; RECALL AND PRECISION; RECOGNITION OF ANATOMICAL NAMES; VESSEL STRUCTURE;

BLOOD VESSELS;

ABDOMINAL ARTERY; ABDOMINAL SURGERY; ANATOMY; ARTERIOSCLEROSIS; ARTERY; ARTICLE; AUTOMATION; CLINICAL ARTICLE; COMPUTER ASSISTED TOMOGRAPHY; HEPATIC ARTERY; HEPATIC PORTAL SYSTEM; HUMAN; MACHINE LEARNING; PORTAL VEIN; PRIORITY JOURNAL; STOMACH CANCER; ABDOMEN; ABDOMINAL RADIOGRAPHY; ANATOMY AND HISTOLOGY; LIVER; VASCULARIZATION;

LABELING; STRUCTURES; TREES;

ABDOMEN; AUTOMATION; HUMANS; LIVER; PORTAL SYSTEM; RADIOGRAPHY, ABDOMINAL; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84920915141     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2014.11.002     Document Type: Article

References (25)

1. Baumhauer M., Feuerstein M., Meinzer H.-P., Rassweiler J. Navigation in endoscopic soft tissue surgery: perspectives and limitations. J. Endourol. 2008, 22(4):751-766.
2. Bilgel, M., Roy, S., Carass, A., Nyquist, P.A., Prince, J.L., 2013. Automated anatomical labeling of the cerebral arteries using belief propagation. In: Proc. SPIE, vol. 8669, pp. 866918-866918-6.
3. Bogunović H., Pozo J., Cárdenes R., San Roman L., Frangi A. Anatomical labeling of the circle of willis using maximum a posteriori probability estimation. IEEE Trans. Med. Imag. 2013, 32(9):1587-1599.
4. Drechsler, K., Laura, C.O., 2011. Simulation of portal vein clamping and the impact of safety margins for liver resection planning. In: Abdominal Imaging, pp. 149-156.
5. Farag, A., Liu, J., Summers, R.M., 2014. Automatic segmentation of abdominal vessels for improved pancreas localization. In: Proc. SPIE, pp. 90371M-1-7.
6. Hoang, B.H., Oda, M., Jiang, Z., Kitasaka, T., Misawa, K., Fujiwara, M., Mori, K., 2011. A study on automated anatomical labeling to arteries concerning with colon from 3D abdominal CT images. In: Proc. SPIE, vol. 7962, pp. 79623R-79623R-9.
7. Li L. Multiclass boosting with repartitioning. ICML '06 2006, 569-576. ACM, New York, NY, USA.
8. Liu A., Tendick F., Cleary K., Kaufmann C. A survey of surgical simulation: applications, technology, and education. Presence: Teleoper. Virtual Environ. 2003, 12(6):599-614.
9. Lu, L., Bi, J., Yu, S., Peng, Z., Krishnan, A., Zhou, X.S., 2009. Hierarchial learning for tubular structure parsing in medical imaging: a study on coronary arteries using 3D CT angiography. In: IEEE 12th International Conference on Computer Vision 2009, pp. 2021-2128.
10. Mezger U., Jendrewski C., Bartels M. Navigation in surgery. Langenbeck's Arch. Surg. 2013, 398(4):501-514.
11. Mori K., Hasegawa J., Suenaga Y., Toriwaki J. Automated anatomical labeling of the bronchial branch and its application to the virtual bronchoscopy system. IEEE Trans. Med. Imag. 2000, 19(2):103-114.
12. Mori, K., Ema, S., Kitasaka, T., Mekada, Y., Ide, I., Murase, H., Suenaga, Y., Takabatake, H., Mori, M., Natori, H., 2005. Automated nomenclature of bronchial branches extracted from CT images and its application to biopsy path planning in virtual bronchoscopy. In: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005, Lecture Notes in Computer Science, vol. 3750, pp. 854-861.
13. Mori, K., Ota, S., Deguchi, D., Kitasaka, T., Suenaga, Y., Iwano, S., Hasegawa, Y., Takabatake, H., Mori, M., Natori, H., 2009. Automated anatomical labeling of bronchial branches extracted from ct datasets based on machine learning and combination optimization and its application to bronchoscope guidance. In: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009, Lecture Notes in Computer Science, vol. 5762, pp. 707-714.
14. Mori, K., Oda, M., Egusa, T., Jiang, Z., Kitasaka, T., Fujiwara, M., Misawa, K., 2010. Automated nomenclature of upper abdominal arteries for displaying anatomical names on virtual laparoscopic images. In: Medical Imaging and Augmented Reality, Lecture Notes in Computer Science, vol. 6326, pp. 353-362.
15. Nimura, Y., Kitasaka, T., Mori, K., 2010. Blood vessel segmentation using line-direction vector based on hessian analysis. In: Proc. SPIE, vol. 7623, pp. 76233Q-76233Q-9.
16. Pamulapati, V., Wood, B.J., Linguraru, M.G., 2011. Intra-hepatic vessel segmentation and classification in multi-phase ct using optimized graph cuts. In: IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2011, pp. 1982-1985.
17. Robben D., Sunaert S., Thijs V., Wilms G., Maes F., Suetens P. Anatomical labeling of the circle of willis using maximum a posteriori graph matching. Lecture Notes in Computer Science 2013, vol. 8149:566-573. Springer, Berlin Heidelberg. K. Mori, I. Sakuma, Y. Sato, C. Barillot, N. Navab (Eds.).
18. Saito T., Toriwaki J.-I. New algorithms for euclidean distance transformation of an n-dimensional digitized picture with applications. Pattern Recogn. 1994, 27(11):1551-1565.
19. Saito, T., Toriwaki, J., 1995. A sequential thinning algorithm for three dimensional digital pictures using the euclidean distance transformation. In: Proc. 9th SCIA (Scandinavian Conf. on Image Analysis), pp. 507-516.
20. Shinoda, T., Kitasaka, T., Mori, K., Suenaga, Y., Misawa, K., Fujiwara, M., 2008. A study on automated anatomical labeling of abdominal arteries extracted from 3D abdominal CT images. Technical report of IEICE. PRMU, vol. 107 (539), pp. 145-150.
21. Stefanidis D., Colavita P. Simulation in general surgery. The Comprehensive Textbook of Healthcare Simulation 2013, 353-366. Springer, New York. A.I. Levine, S. DeMaria, A.D. Schwartz, A.J. Sim (Eds.).
22. Suzuki Y., Okada T., Hori M., Yokota F., Linguraru M., Tomiyama N., Sato Y. Automated anatomical labeling of abdominal arteries from CT data based on optimal path finding between segmented organ and aorta regions: a robust method against topological variability. Int. J. CARS 2012, 7(1):S47-S48.
23. Tao Y., Peng Z., Krishnan A., Zhou X.S. Robust learning-based parsing and annotation of medical radiographs. IEEE Trans. Med. Imag. 2011, 30:338-350.
24. Tschirren J., McLennan G., Pálágyi K., Hoffman E., Sonka M. Matching and anatomical labeling of human airway tree. IEEE Trans. Med. Imag. 2005, 24(12):1540-1547.
25. Uchiyama, Y., Yamauchi, M., Ando, H., Yokoyama, R., Hara, T., Fujita, H., Iwama, T., Hoshi, H., 2006. Automated classification of cerebral arteries in MRA images and its application to maximum intensity projection. In: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006, EMBS '06, pp. 4865-4868.