Cognition Network Technology for a Fully Automated 3D Segmentation of Liver Tumors
The Definiens Cognition Network Technology is applied to detect automatically tumors in a human liver. On the basis of a test data set containing ten tumors we show first quantitative results which are compared to manual segmentations provided by medical [...]

A semi-automated method for liver tumor segmentation based on 2D region growing with
Liver tumour segmentation from computed tomography (CT) scans is a challenging task. A semi-automatic method based on 2D region growing with knowledge-based constraints is proposed to segment lesions from constituent 2D slices obtained from 3D CT images. [...]

An iterative Bayesian approach for liver analysis: tumors validation study
We present a new method for the simultaneous, nearly automatic segmentation of liver contours, vessels, and tumors from abdominal CTA scans. The method repeatedly applies multi-resolution, multi-class smoothed Bayesian classification followed by [...]

Semi-automatic Segmentation of 3D Liver Tumors from CT Scans Using Voxel Classification and Propagational Learning
A semi-automatic scheme was developed for the segmentation of 3D liver tumors from computed tomography (CT) images. First a support vector machine (SVM) classifier was trained to extract tumor region from one single 2D slice in the intermediate part of a [...]

Segmentation of Liver Metastases Using a Level Set Method with Spiral-Scanning Technique and Supervised Fuzzy Pixel Classification
In this paper a specific method is presented to facilitate the semi-automatic segmentation of liver metastases in CT images. Accurate and reliable segmentation of tumors is e.g. essential for the follow-up of cancer treatment. The core of the algorithm is a [...]

Semi-automatic Segmentation of Liver Tumors from CT Scans Using Bayesian Rule-based 3D Region Growing
Automatic segmentation of liver tumorous regions often fails due to high noise and large variance of tumors. In this work, a semi-automatic algorithm is proposed to segment liver tumors from computed tomography (CT) images. To cope with the variance of [...]

Contrast Enhancement for Liver Tumor Identification
In CT images, tumors located in a liver are generally identified by intensity difference between tumor and liver. The intensity of the tumor can be lower and or higher than that of the liver. However, the main problem of liver tumor detection from is related [...]

Fostering Open Science in Lung Cancer Lesion Sizing with ITK module LSTK
This document describes the latest efforts in integrating the Lesion Sizing Toolkit (LSTK) into ITK v4 as an external/remote module providing an Open Science dashboard website with a large open image archive of lung cancer CT images for LSTK development and [...]

Multimodal Analysis of Vasogenic Edema in Glioblastoma Patients for Radiotherapy Planning
No opinion
Glioblastoma (GBM) is the most common type of primary brain tumor, which is characterized by an infiltrative growth pattern. In current practice, radiotherapy planning is primarily based upon T2 FLAIR MRI despite its known lack of specificity in the detection [...]

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