@inproceedings{ca577fc03183480e8c38311cbac62957,
title = "Liver metastasis early detection using fMRI based statistical model",
abstract = "We present a novel method for computer aided early detection of liver metastases. The method used fMRI-based statistical modeling to characterize colorectal hepatic metastases and follow their early hemodynamical changes. Changes in hepatic hemodynamics were evaluated from T2*-W fMRI images acquired during the breathing of air, air-CO2, and carbogen. A classification model was built to differentiate between metastatic and healthy liver tissue. The model was constructed from 128 validated fMRI samples of metastatic and healthy mice liver tissue using histogram-based features and SVM classification engine. The model was subsequently tested with a set of 32 early, non-validated fMRI samples. Our model yielded an accuracy of 84.38\% with 80\% precision.",
keywords = "Computer-aided diagnosis, Early detection, Liver metastasis, Statistical analysis, fMRI analysis",
author = "Moti Freiman and Yifat Edrei and Eitan Gross and Leo Joskowicz and Rinat Abramovitch",
year = "2008",
doi = "10.1109/ISBI.2008.4541063",
language = "אנגלית",
isbn = "9781424420032",
series = "2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI",
publisher = "IEEE Computer Society",
pages = "584--587",
booktitle = "2008 5th IEEE International Symposium on Biomedical Imaging",
address = "ארצות הברית",
note = "5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2008 ; Conference date: 14-05-2008 Through 17-05-2008",
}