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MICCAI
2010
Springer
8 years 7 months ago
A Generative Model for Brain Tumor Segmentation in Multi-Modal Images
Abstract. We introduce a generative probabilistic model for segmentation of tumors in multi-dimensional images. The model allows for different tumor boundaries in each channel, ref...
Bjoern H. Menze, Koenraad Van Leemput, Danial Lash...
TMI
2010
113views more  TMI 2010»
8 years 7 months ago
Multiscale Model of Liver DCE-MRI Towards a Better Understanding of Tumor Complexity
Abstract—The use of quantitative imaging for the characterization of hepatic tumors in MRI can improve the diagnosis and therefore the treatment of these life-threatening tumors....
Muriel Mescam, Marek Kretowski, Johanne Béz...
TMI
2008
123views more  TMI 2008»
8 years 9 months ago
ORBIT: A Multiresolution Framework for Deformable Registration of Brain Tumor Images
Abstract--A deformable registration method is proposed for registering a normal brain atlas with images of brain tumor patients. The registration is facilitated by first simulating...
Evangelia I. Zacharaki, Dinggang Shen, Seung-koo L...
BMCBI
2006
126views more  BMCBI 2006»
8 years 9 months ago
A minimally invasive multiple marker approach allows highly efficient detection of meningioma tumors
Background: The development of effective frameworks that permit an accurate diagnosis of tumors, especially in their early stages, remains a grand challenge in the field of bioinf...
Andreas Keller, Nicole Ludwig, Nicole Comtesse, An...
CGF
2010
148views more  CGF 2010»
8 years 9 months ago
Visual Support for Interactive Post-Interventional Assessment of Radiofrequency Ablation Therapy
Teaser Figure: A volume rendering with the corresponding tumor map, a pseudo-cylindrical mapping of the tumor surface. Percutaneous radiofrequency (RF) ablation is a minimally inv...
Christian Rieder, Andreas Weihusen, Christian Schu...
BMCBI
2010
148views more  BMCBI 2010»
8 years 9 months ago
Applying unmixing to gene expression data for tumor phylogeny inference
Background: While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall int...
Russell Schwartz, Stanley Shackney
BIOINFORMATICS
2010
138views more  BIOINFORMATICS 2010»
8 years 9 months ago
Robust unmixing of tumor states in array comparative genomic hybridization data
Motivation: Tumorigenesis is an evolutionary process by which tumor cells acquire sequences of mutations leading to increased growth, invasiveness, and eventually metastasis. It i...
David Tolliver, Charalampos E. Tsourakakis, Ayshwa...
ICMLA
2008
8 years 10 months ago
Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques
Accurate lung tumor targeting in real time plays a fundamental role in image-guide radiotherapy of lung cancers. Precise tumor targeting is required for both respiratory gating an...
Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconc...
EUROMICRO
2000
IEEE
9 years 1 months ago
Tumor Recognition in Endoscopic Video Images Using Artificial Neural Network Architectures
This paper focuses on a scheme for automated tumor recognition using images acquired during endoscopic sessions. The proposed recognition system is based on multi-layer feed forwa...
S. A. Karkanis, Dimitrios K. Iakovidis, Dimitrios ...
MICCAI
2004
Springer
9 years 2 months ago
Determining Malignancy of Brain Tumors by Analysis of Vessel Shape
Abstract. Vessels supplying malignant tumors are abnormally shaped. This paper describes a blinded study that assessed tumor malignancy by analyzing vessel shape within MR images o...
Elizabeth Bullitt, Inkyung Jung, Keith E. Muller, ...
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