Segmentation of Liver Metastases in CT Scans by Adaptive Thresholding and Morphological Processing-Reference-Cited by-同舟云学术

Segmentation of Liver Metastases in CT Scans by Adaptive Thresholding and Morphological Processing

Published:2008-07-07 Issue: Volume: Page:
ISSN:
Container-title:The MIDAS Journal
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Author:

Moltz Jan hendrik,Bornemann Lars,Dicken Volker,Peitgen Heinz-Otto

Abstract

This article presents an algorithm for the segmentation of liver metastases in CT scans. It is a hybrid method that combines adaptive thresholding based on a gray value analysis of the ROI with model-based morphological processing. We show the results of the MICCAI liver tumor segmentation competition 2008 which were successful for all ten tumors.

Publisher

NumFOCUS - Insight Software Consortium (ITK)

Reference9 articles.

1. Liver Tumor Volume Estimation By Semi-Automatic Segmentation Method

2. Automatic Hepatic Tumor Segmentation Using Statistical Optimal Threshold

3. Automatic Segmentation of Single and Multiple Neoplastic Hepatic Lesions in CT Images

4. A Machine Learning Approach for Locating Boundaries of Liver Tumors in CT Images

5. Simultaneous detection of multiple elastic surfaces with application to tumor segmentation in CT images

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