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» Two Methods for Validating Brain Tissue Classifiers
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ISNN
2004
Springer
14 years 1 months ago
Unsupervised Learning for Hierarchical Clustering Using Statistical Information
This paper proposes a novel hierarchical clustering method that can classify given data without specified knowledge of the number of classes. In this method, at each node of a hie...
Masaru Okamoto, Nan Bu, Toshio Tsuji
BMCBI
2006
165views more  BMCBI 2006»
13 years 7 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin
BMCBI
2002
147views more  BMCBI 2002»
13 years 7 months ago
Expression profiling of human renal carcinomas with functional taxonomic analysis
Background: Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies...
Michael A. Gieseg, Theresa Cody, Michael Z. Man, S...
MICCAI
2009
Springer
14 years 4 months ago
Fast Automatic Segmentation of the Esophagus from 3D CT Data Using a Probabilistic Model
Automated segmentation of the esophagus in CT images is of high value to radiologists for oncological examinations of the mediastinum. It can serve as a guideline and prevent confu...
Johannes Feulner, Shaohua Kevin Zhou, Alexander Ca...
APVIS
2009
13 years 8 months ago
Visualizing diffusion tensor imaging data with merging ellipsoids
Diffusion tensor fields reveal the underlying anatomical structures in biological tissues such as neural fibers in the brain. Most current methods for visualizing the diffusion te...
Wei Chen, Song Zhang, Stephen Correia, David F. Ta...