SIMPLE is a good idea (and better with context learning)

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8673 LNCS, Issue PART 1, 2014, Pages 364-371

  Xu, Zhoubing ^a   Asman, Andrew J ^a   Shanahan, Peter L ^b   Abramson, Richard G ^b   Landman, Bennett A ^a,b  

^a VANDERBILT UNIVERSITY   (United States)

^b VANDERBILT UNIVERSITY   (United States)

Author keywords

Abdomen; Context Learning; Multi Atlas Segmentation; Selective and Iterative Method for Performance Level Estimation (SIMPLE)

Indexed keywords

ITERATIVE METHODS; COMPUTERIZED TOMOGRAPHY; MEDICAL COMPUTING; MEDICAL IMAGING;

ABDOMEN; CONTEXT LEARNING; METASTATIC LIVER CANCERS; PERFORMANCE LEVEL; RADIOTHERAPY PLANNING; SEGMENTATION TECHNIQUES; SIMILARITY COEFFICIENTS; STATISTICAL LITERATURE;

COMPUTERIZED TOMOGRAPHY; ITERATIVE METHODS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE ENHANCEMENT; LIVER TUMOR; METASTASIS; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SPLEEN TUMOR;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE ENHANCEMENT; LIVER NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPLENIC NEOPLASMS; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84906983948     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10404-1_46     Document Type: Conference Paper

References (12)

1. Wolz, R., Chu, C., Misawa, K., Fujiwara, M., Mori, K., Rueckert, D.: Automated abdominal multi-organ segmentation with subject-specific atlas generation. IEEE Transactions on Medical Imaging 32, 1723-1730 (2013)
2. Sabuncu, M.R., Yeo, B.T., Van Leemput, K., Fischl, B., Golland, P.: A generative model for image segmentation based on label fusion. IEEE Transactions on Medical Imaging 29, 1714-1729 (2010)
3. Langerak, T.R., van der Heide, U.A., Kotte, A.N., Viergever, M.A., van Vulpen, M., Pluim, J.P.: Label fusion in atlas-based segmentation using a selective and iterative method for performance level estimation (SIMPLE). IEEE Transactions on Medical Imaging 29, 2000-2008 (2010)
4. Dice, L.R.: Measures of the amount of ecologic association between species. Ecology 26, 297-302 (1945)
5. Warfield, S.K., Zou, K.H., Wells, W.M.: Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Transactions on Medical Imaging 23, 903-921 (2004)
6. Rohlfing, T., Brandt, R., Menzel, R., Maurer Jr., C.R.: Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains. NeuroImage 21, 1428-1442 (2004)
7. Wang, H., Suh, J.W., Das, S.R., Pluta, J., Craige, C., Yushkevich, P.A.: Multi-Atlas Segmentation with Joint Label Fusion. IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
8. Asman, A.J., Landman, B.A.: Robust statistical label fusion through COnsensus Level, Labeler Accuracy, and Truth Estimation (COLLATE). IEEE Transactions on Medical Imaging 30, 1779-1794 (2011)
9. Van Leemput, K., Maes, F., Vandermeulen, D., Suetens, P.: Automated model-based bias field correction of MR images of the brain. IEEE Trans. Med. Imaging 18, 885-896 (1999)
10. McAuliffe, M.J., Lalonde, F.M., McGarry, D., Gandler, W., Csaky, K., Trus, B.L.: Medical image processing, analysis and visualization in clinical research. In: Proceedings of the 14th IEEE Symposium on Computer-Based Medical Systems, pp. 381-386. IEEE (2001)
11. Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L.G., Leach, M.O., Hawkes, D.J.: Nonrigid registration using free-form deformations: Application to breast MR images. IEEE Trans. Med. Imaging 18, 712-721 (1999)
12. Jorge Cardoso, M., Leung, K., Modat, M., Keihaninejad, S., Cash, D., Barnes, J., Fox, N.C., Ourselin, S.: STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation. Med. Image Anal. 17, 671-684 (2013)