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Characterization of renal tumours based on Raman spectra classification

Authors :
Julien Fleureau
Olivier Lavastre
Renaud de Crevoisier
Karim Bensalah
Lotfi Senhadji
Jean-Jacques Patard
Nathalie Rioux-Leclercq
Francois Guille
Denis Rolland
Laboratoire Traitement du Signal et de l'Image (LTSI)
Université de Rennes 1 (UR1)
Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Institut des Sciences Chimiques de Rennes (ISCR)
Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Rennes 1 (UR1)
Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)
Service d'urologie [Rennes] = Urology [Rennes]
Hôpital Pontchaillou-CHU Pontchaillou [Rennes]
This work is supported by the National Research Agency of France (ANR) under the Grants DIAPRECA ANR-06-TecSan-013-01 and ANR-06-TecSan-013-03.
Le Corre, Morgane
Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)
Source :
Expert Systems with Applications, Expert Systems with Applications, Elsevier, 2011, 38 (11), pp.14301-14306. ⟨10.1016/j.eswa.2011.05.092⟩, Expert Systems with Applications, 2011, 38 (11), pp.14301-14306. ⟨10.1016/j.eswa.2011.05.092⟩
Publication Year :
2011
Publisher :
HAL CCSD, 2011.

Abstract

International audience; In this study, we propose to evaluate the potential of Raman spectroscopy (RS) to assess renal tumours at surgery. Different classes of Raman renal spectra acquired during a clinical protocol are discriminated using support vector machines classifiers. The influence on the classification scores of various preprocessing steps generally involved in RS are also investigated and evaluated in the particular context of renal tumour characterization. Encouraging results show the interest of RS to evaluate kidney cancer and suggest the potential of this technique as a surgical assistance during partial nephrectomy.

Details

Language :
English
ISSN :
09574174
Database :
OpenAIRE
Journal :
Expert Systems with Applications, Expert Systems with Applications, Elsevier, 2011, 38 (11), pp.14301-14306. ⟨10.1016/j.eswa.2011.05.092⟩, Expert Systems with Applications, 2011, 38 (11), pp.14301-14306. ⟨10.1016/j.eswa.2011.05.092⟩
Accession number :
edsair.doi.dedup.....a44248cc519585e623da9b93756faaca