Semi-supervised and active learning for automatic segmentation of Crohn's disease

Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A.W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann

doi:10.1007/978-3-642-40763-5_27

Semi-supervised and active learning for automatic segmentation of Crohn's disease

Dwarikanath Mahapatra, Peter J. Schüffler, Jeroen A.W. Tielbeek, Franciscus M. Vos, Joachim M. Buhmann

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

27 Scopus citations

Abstract

Our proposed method combines semi supervised learning (SSL) and active learning (AL) for automatic detection and segmentation of Crohn's disease (CD) from abdominal magnetic resonance (MR) images. Random forest (RF) classifiers are used due to fast SSL classification and capacity to interpret learned knowledge. Query samples for AL are selected by a novel information density weighted approach using context information, semantic knowledge and labeling uncertainty. Experimental results show that our proposed method combines the advantages of SSL and AL, and with fewer samples achieves higher classification and segmentation accuracy over fully supervised methods.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings
Pages	214-221
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-40763-5_27
State	Published - 2013
Externally published	Yes
Event	16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan Duration: 22 Sep 2013 → 26 Sep 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	8150 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
Country/Territory	Japan
City	Nagoya
Period	22/09/13 → 26/09/13

Access to Document

10.1007/978-3-642-40763-5_27

Cite this

Mahapatra, D., Schüffler, P. J., Tielbeek, J. A. W., Vos, F. M., & Buhmann, J. M. (2013). Semi-supervised and active learning for automatic segmentation of Crohn's disease. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings (PART 2 ed., pp. 214-221). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8150 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-40763-5_27

Mahapatra, Dwarikanath ; Schüffler, Peter J. ; Tielbeek, Jeroen A.W. et al. / Semi-supervised and active learning for automatic segmentation of Crohn's disease. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. PART 2. ed. 2013. pp. 214-221 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{e6af0a2f7c7843d7becfc7cef716ae29,

title = "Semi-supervised and active learning for automatic segmentation of Crohn's disease",

abstract = "Our proposed method combines semi supervised learning (SSL) and active learning (AL) for automatic detection and segmentation of Crohn's disease (CD) from abdominal magnetic resonance (MR) images. Random forest (RF) classifiers are used due to fast SSL classification and capacity to interpret learned knowledge. Query samples for AL are selected by a novel information density weighted approach using context information, semantic knowledge and labeling uncertainty. Experimental results show that our proposed method combines the advantages of SSL and AL, and with fewer samples achieves higher classification and segmentation accuracy over fully supervised methods.",

author = "Dwarikanath Mahapatra and Sch{\"u}ffler, {Peter J.} and Tielbeek, {Jeroen A.W.} and Vos, {Franciscus M.} and Buhmann, {Joachim M.}",

year = "2013",

doi = "10.1007/978-3-642-40763-5_27",

language = "English",

isbn = "9783642407628",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 2",

pages = "214--221",

booktitle = "Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings",

edition = "PART 2",

note = "16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 ; Conference date: 22-09-2013 Through 26-09-2013",

}

Mahapatra, D, Schüffler, PJ, Tielbeek, JAW, Vos, FM & Buhmann, JM 2013, Semi-supervised and active learning for automatic segmentation of Crohn's disease. in Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 8150 LNCS, pp. 214-221, 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, Nagoya, Japan, 22/09/13. https://doi.org/10.1007/978-3-642-40763-5_27

Semi-supervised and active learning for automatic segmentation of Crohn's disease. / Mahapatra, Dwarikanath; Schüffler, Peter J.; Tielbeek, Jeroen A.W. et al.
Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. PART 2. ed. 2013. p. 214-221 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8150 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Semi-supervised and active learning for automatic segmentation of Crohn's disease

AU - Mahapatra, Dwarikanath

AU - Schüffler, Peter J.

AU - Tielbeek, Jeroen A.W.

AU - Vos, Franciscus M.

AU - Buhmann, Joachim M.

PY - 2013

Y1 - 2013

N2 - Our proposed method combines semi supervised learning (SSL) and active learning (AL) for automatic detection and segmentation of Crohn's disease (CD) from abdominal magnetic resonance (MR) images. Random forest (RF) classifiers are used due to fast SSL classification and capacity to interpret learned knowledge. Query samples for AL are selected by a novel information density weighted approach using context information, semantic knowledge and labeling uncertainty. Experimental results show that our proposed method combines the advantages of SSL and AL, and with fewer samples achieves higher classification and segmentation accuracy over fully supervised methods.

AB - Our proposed method combines semi supervised learning (SSL) and active learning (AL) for automatic detection and segmentation of Crohn's disease (CD) from abdominal magnetic resonance (MR) images. Random forest (RF) classifiers are used due to fast SSL classification and capacity to interpret learned knowledge. Query samples for AL are selected by a novel information density weighted approach using context information, semantic knowledge and labeling uncertainty. Experimental results show that our proposed method combines the advantages of SSL and AL, and with fewer samples achieves higher classification and segmentation accuracy over fully supervised methods.

UR - http://www.scopus.com/inward/record.url?scp=84885904347&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-40763-5_27

DO - 10.1007/978-3-642-40763-5_27

M3 - Conference contribution

C2 - 24579143

AN - SCOPUS:84885904347

SN - 9783642407628

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 214

EP - 221

BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings

T2 - 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013

Y2 - 22 September 2013 through 26 September 2013

ER -

Mahapatra D, Schüffler PJ, Tielbeek JAW, Vos FM, Buhmann JM. Semi-supervised and active learning for automatic segmentation of Crohn's disease. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. PART 2 ed. 2013. p. 214-221. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-40763-5_27

Semi-supervised and active learning for automatic segmentation of Crohn's disease

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this