Automated prediction of Glasgow outcome scale for traumatic brain injury

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2014, Pages 3245-3250

  Sut, Bolan ^b   Dinh, Thien Anh ^a   Ambastha, Abhinit Kumar ^a   Gong, Tianxia ^a   Silander, Tomi ^a   Lu, Shijian ^b   Lim, C C Tchoyoson ^c   Pang, Boon Chuan ^c   Lee, Cheng Kiang ^c   Leong, Tze Yun ^a   Tan, Chew Lim ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^c TAN TOCK SENG HOSPITAL   (Singapore)

Author keywords

Brain CT Scan; Glasgow Outcome Scale; Logistic Regression; Sparse Representation Classifier

Indexed keywords

AUTOMATION; BRAIN; FORECASTING; LARGE DATASET; LOGISTIC REGRESSION; PATTERN RECOGNITION;

BRAIN CT; CLINICAL FEATURES; COMPUTERIZED PREDICTION; GLASGOW OUTCOME SCALE; PRE-PROCESSED DATA; PREDICTION SYSTEMS; SPARSE REPRESENTATION; TRAUMATIC BRAIN INJURIES;

COMPUTERIZED TOMOGRAPHY;

EID: 84919934759     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2014.559     Document Type: Conference Paper

References (30)

1. D. Cosic and S. Loncaric, Rule-based labeling of CT head image, ser. Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1997, vol. 1211, ch. 49, pp. 453-456.
2. W. A. Knaus, E. A. Draper, D. P. Wagner, and J. E. Zimmerman, "Apache ii: A severity of disease classification system," Crit Care Med, vol. 13, no. 10, pp. 818-29, 1985.
3. W. A. Knaus, D. P. Wagner, E. A. Draper, J. E. Zimmerman, M. Bergner, P. G. Bastos, C. A. Sirio, D. J. Murphy, T. Lotring, A. Damiano, and et al., "The apache iii prognostic system. risk prediction of hospital mortality for critically ill hospitalized adults," Chest, vol. 100, no. 6, pp. 1619-36, 1991.
4. J. M. Boone, "Radiological interpretation 2020: toward quantitative image assessment," Med Phys, vol. 34, no. 11, pp. 4173-9, 2007.
5. D. C. Sullivan, "Imaging as a quantitative science," Radiology, vol. 248, no. 2, pp. 328-332, 2008.
6. J. Silver, T. McAllister, and S. Yudofsky, Textbook of Traumatic Brain Injury. American Psychiatric Pub., 2011.
7. B. Jennett and M. Bond, "Assessment of outcome after severe brain damage," Lancet, vol. 1, no. 7905, pp. 480-4, 1975.
8. D. A. Ross, W. L. Olsen, A. M. Ross, B. T. Andrews, and L. H. Pitts, "Brain shift, level of consciousness, and restoration of consciousness in patients with acute intracranial hematoma," J Neurosurg, vol. 71, no. 4, pp. 498-502, 1989.
9. H. K. Sucu, F. Gelal, M. Gokmen, F. D. Ozer, and S. Tektas, "Can midline brain shift be used as a prognostic factor to predict postoperative restoration of consciousness in patients with chronic subdural hematoma?" Surg Neurol, vol. 66, no. 2, pp. 178-82, 2006.
10. B. T. Andrews, r. Chiles, B. W., W. L. Olsen, and L. H. Pitts, "The effect of intracerebral hematoma location on the risk of brain-stem compression and on clinical outcome," J Neurosurg, vol. 69, no. 4, pp. 518-22, 1988.
11. L. F. Marshall, S. B. Marshall, M. R. Klauber, M. v. B. Clark, H. M. Eisenberg, J. A. Jane, T. G. Luerssen, A. Marmarou, and M. A. Foulkes, "A new classification of head injury based on computerized tomography," Special Supplements, vol. 75, no. 1s, pp. S14-S20, 1991.
12. A. I. Maas, C. W. Hukkelhoven, L. F. Marshall, and E. W. Steyerberg, "Prediction of outcome in traumatic brain injury with computed tomographic characteristics: A comparison between the computed tomographic classification and combinations of computed tomographic predictors," Neurosurgery, vol. 57, no. 6, pp. 1173-82, 2005.
13. R. Liu, C. L. Tan, T.-Y. Leong, C. K. Lee, B. C. Pang, C. C. T. Lim, Q. Tian, S. Tang, and Z. Zhang, "Hemorrhage slices detection in brain ct images," in Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, 2008, pp. 1-4.
14. T. Gong, S. Li, J. Wang, C.-L. Tan, B. C. Pang, C. C. T. Lim, C. K. Lee, Q. Tian, and Z. Zhang, "Automatic labeling and classification of brain ct images," in Image Processing (ICIP), 2011 18th IEEE International Conference on, 2011, pp. 1581-1584.
15. T. A. Dinh, T. Silander, C. C. Lim, and T. Y. Leong, "An automated pathological class level annotation system for volumetric brain images," AMIA Annu Symp Proc, pp. 1201-10, 2012.
16. B. Liu, Q. Yuan, Z. Liu, X. Li, and X. Yin, "Automatic segmentation of intracranial hematoma and volume measurement," Conf Proc IEEE Eng Med Biol Soc, vol. 2008, pp. 1214-7, 2008.
17. F. Xiao, C. C. Liao, K. C. Huang, I. J. Chiang, and J. M. Wong, "Automated assessment of midline shift in head injury patients," Clin Neurol Neurosurg, vol. 112, no. 9, pp. 785-90, 2010.
18. B. Jacobs, T. Beems, T. M. van der Vliet, R. R. Diaz-Arrastia, G. F. Borm, and P. E. Vos, "Computed tomography and outcome in moderate and severe traumatic brain injury: hematoma volume and midline shift revisited," J Neurotrauma, vol. 28, no. 2, pp. 203-15, 2011.
19. "Head injury prognosis: Crash," http://www. crash. lshtm. Ac. uk/Risk calculator/index. html.
20. "Prediction models for 6 month outcome after tbi," http://survey. erasmusmc. nl/impact/index. php?id=1. 0. 0. 1. 0. 0.
21. T. A. Dinh, T. Silander, B. Su, T. Gong, B. C. Pang, C. C. T. Lim, C. K. Lee, C. L. Tan, and T.-Y. Leong, "Unsupervised medical image classification by combining case-based classifiers," Medinfo 2013, to appear.
22. H. Feichtinger and T. Strohmer, Gabor Analysis and Algorithms: Theory and Applications. Birkhauser, 1998.
23. K. Huang and S. Aviyente, "Sparse representation for signal classification," Advances in neural information processing systems, vol. 19, p. 609, 2007.
24. C. W. P. M. Hukkelhoven, E. W. Steyerberg, J. D. F. Habbema, E. Farace, A. Marmarou, G. D. Murray, L. F. Marshall, and A. I. R. Maas, "Predicting outcome after traumatic brain injury: development and validation of a prognostic score based on admission characteristics," Journal of Neurotrauma, vol. 22, no. 10, pp. 1025-39, Oct. 2005.
25. N. A. Mushkudiani, C. W. P. M. Hukkelhoven, A. V. Hernández, G. D. Murray, S. C. Choi, A. I. R. Maas, and E. W. Steyerberg, "A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes," Journal of Clinical Epidemiology, vol. 61, no. 4, pp. 331-43, Apr. 2008.
26. A. Jain and G. Healey, "A multiscale representation including opponent color features for texture recognition," Image Processing, IEEE Transactions on, vol. 7, no. 1, pp. 124-128, 1998.
27. J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and M. Yi, "Robust face recognition via sparse representation," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 31, no. 2, pp. 210-227, 2009.
28. K. Koh, S.-J. Kim, and S. Boyd, "An interior-point method for largescale l1-regularized logistic regression," Journal of Machine learning research, vol. 8, no. 8, pp. 1519-1555, 2007.
29. C.-G. Li, J. Guo, and H.-G. Zhang, "Local sparse representation based classification," in Pattern Recognition (ICPR), 2010 20th International Conference on. IEEE, pp. 649-652.
30. J. A. Nelder and R. W. Wedderburn, "Generalized linear models," Journal of the Royal Statistical Society. Series A (General), pp. 370-384, 1972.