Abstract:
We  present a machine-learning approach to the interactive classification of suspected liver metastases in fMRI images. The

method uses fMRI-based statistical modeling to characterize colorectal hepatic metastases and follow their early hemodynamical changes.
Changes in hepatic hemodynamics are evaluated from T2 -W fMRI images acquired during the breathing of air, air-CO2, and carbogen.
A classification model is build to differentiate between tumors and healthy liver tissues. To validate our method, a model was built from 29 mice
datasets, and used to classify suspicious regions in 16 new datasets of healthy subjects or subjects with metastases in earlier growth phases.
Our experimental results on mice yielded an accuracy of 78% with high precision (88%). This suggests that the method can provide a useful aid
for early detection of liver metastases.

Keywords: Computer aided early detection, fMRI analysis, liver tumors, tumor statistical model

Project publications:

• Freiman, M.,  Edrei, Y., Sela, Y., Shmidmayer, Y., Gross, E.,  Joskowicz, L. and   Abramovitch,  R., "Classification of suspected liver metastases using fMRI images: a machine learning approach",
  In Proc. of the 11th Int. Conf. of Medical Image Computing and Computed Aided Interventions (MICCAI'08) , (pdf).
  
  
• Freiman, M.,  Edrei, Y., Gross, E.,  Joskowicz, L. and   Abramovitch,  R., "Liver metastases early detection using fMRI based statistical model",
  In Proc. of the 5th IEEE Int. Symposium on Biomedical Imaging: From Nano to Macro. ISBI'08. (pdf)  
  
  (Copyright 2008 IEEE. Published in the 2008 International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2008), scheduled for May 14-17, 2008 in Paris, France Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyrights and Permissions / IEEE Service Center / 445 Hoes Lane / P.O. Box 1331 / Piscataway, NJ 08855-1331, USA. Telephone: + Intl. 908-562-3966.)
  
  
• Freiman, M.,  Edrei, Y., Gross, E.,  Joskowicz, L. and,   Abramovitch,  R., "Computer assisted early detection of liver metastases from fMRI maps",
  In Proc. of  the  21th Int. Conf. on Computer Assisted Radiology and Surgery. CARS'07.  (pdf)

Related materials:

• ISBI'08 poster (pdf).
• CARS 2007 presentation (ppt).

Links:

• Clinical trials.