Abstract
The workshop Multimodal Retrieval in the Medical Domain (MRMD) took place in connection with the European Conference of Information Retrieval (ECIR) in Vienna, Austria on March 29, 2015. The workshop included two invited presentations and seven accepted scientific papers. A session on the VISCERAL (VISual Concept Extraction in RAdioLogy) Retrieval Benchmark, an information retrieval benchmark combining semantics with 3D images, was included in the workshop and four groups presented their results on the benchmark using the same database and query topics to produce comparable results. The end of the workshop featured a discussion session with the invited speakers and workshop organizers regarding what is now needed to advance large–scale multimodal medical information retrieval.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Riding the wave: How europe can gain from the rising tide of dcientific data. Submission to the European Comission, October 2010. http://cordis.europa.eu/fp7/ict/e-infrastructure/docs/hlg-sdi-report.pdf
Balikas, G., Krithara, A., Partalas, I., Paliouras, G.: BioASQ: a challenge on large-scale biomedical semantic indexing and question answering. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain (MRMD) 2015. LNCS, vol. 9059, pp. 26–39. Springer, Heidelberg (2015)
Choi, S.: Multimodal medical case-based retrieval on the image and report: SNUMedinfo at VISCERAL Benchmark. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain. LNCS, vol. 9059, pp. 124–128. Springer, Heidelberg (2015)
Demner-Fushman, D., Shooshan, S.E., Rodriguez, L., Antani, S., Thoma, G.R.: Annotation of chest radiology reports for indexing and retrieval. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain (MRMD) 2015. LNCS, vol. 9059, pp. 99–111. Springer, Heidelberg (2015)
Hanbury, A., Müller, H., Langs, G., Weber, M.A., Menze, B.H., Fernandez, T.S.: Bringing the algorithms to the data: cloud–based Benchmarking for medical image analysis. In: Catarci, T., Forner, P., Hiemstra, D., Peñas, A., Santucci, G. (eds.) CLEF 2012. LNCS, vol. 7488, pp. 24–29. Springer, Heidelberg (2012)
García Seco de Herrera, A., Markonis, D., Joyseeree, R., Schaer, R., Foncubierta-Rodríguez, A., Müller, H.: Using semi-supervised learning for image modality classification. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain (MRMD) 2015. LNCS, Springer, Heidelberg (2015)
Jiménez-del-Toro, O.A., Cirujeda, P., Cid, Y.D., Müller, H.: RadLex terms and local texture features for multimodal medical case retrival. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain. LNCS, vol. 9059, pp. 144–152. Springer, Heidelberg (2015)
Kurtz, C., Idoux, P.A., Thangali, A., Cloppet, F., Beaulieu, C.F., Rubin, D.L.: Semantic retrieval of radiological images with relevance feedback. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain (MRMD) 2015, vol. 9059 , pp. 11–25. LNCS, Springer, Heidelberg (2015)
Langs, G., Hanbury, A., Menze, B., Müller, H.: VISCERAL: towards large data in medical imaging — challenges and directions. In: Greenspan, H., Müller, H., Syeda-Mahmood, T. (eds.) MCBR-CDS 2012. LNCS, vol. 7723, pp. 92–98. Springer, Heidelberg (2013)
Li, W., Qian, Y., Loomes, M., Gao, X.: The application of KAZE features to the classification of echocardiogram videos. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain (MRMD) 2015. LNCS, vol. 9059, pp. 61–72. Springer, Heidelberg (2015)
Liu, S., Hadi, N., Liu, S., Pujol, S., Kikinis, R., Zhang, F., Feng, D.D., Cai, W.: Content-based retrieval of brain diffusion magnetic resonance image. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain (MRMD) 2015. LNCS, vol. 9059, pp. 54–60. Springer, Heidelberg (2015)
Soualmia, L.F., Lelong, R., Dahamna, B., Darmoni, S.J.: Rewriting natural language queries using patterns. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain (MRMD) 2015. LNCS, vol. 9059. Springer, Heidelberg (2015)
Spanier, A.B., Joskowicz, L.: Medical case-based retrieval of patient records using the radlex hierarchical lexicon. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain. LNCS, vol. 9059, pp. 129–138. Springer, Heidelberg (2015)
Stathopoulos, S., Kalamboukis, T.: Multi-modal indexing and retrieval using an LSA-based kernel. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain (MRMD) 2015. LNCS, vol. 9059, pp. 73–84. Springer, Heidelberg (2015)
Jiménez-del Toro, O.A., Foncubierta-Rodríguez, A., Müller, H., Langs, G., Hanbury, A.: Overview of the VISCERAL retrieval Benchmark 2015. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain. LNCS, vol. 9059, pp. 115–123. Springer, Heidelberg (2015)
Zhang, F., Song, Y., Cai, W., Depeursinge, A., Müller, H.: USYD/HES-SO in the VISCERAL retrieval Benchmark. In: Müller, H. et al. (eds.) Multimodal Retrieval in the Medical Domain. LNCS, vol. 9059, pp. 139–143. Springer, Heidelberg (2015)
Acknowledgments
This work was partially supported by the EU in FP7 via the VISCERAL project (grant agreement 318068).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Müller, H., Jiménez–del–Toro, O., Hanbury, A., Langs, G., Foncubierta–Rodríguez, A. (2015). Overview of the First Workshop of Muldimodal Retrieval in the Medical Domain (MRMD 2015). In: Müller, H., Jimenez del Toro, O., Hanbury, A., Langs, G., Foncubierta Rodriguez, A. (eds) Multimodal Retrieval in the Medical Domain. MRDM 2015. Lecture Notes in Computer Science(), vol 9059. Springer, Cham. https://doi.org/10.1007/978-3-319-24471-6_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-24471-6_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24470-9
Online ISBN: 978-3-319-24471-6
eBook Packages: Computer ScienceComputer Science (R0)