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CVPR
2011
IEEE
14 years 4 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk
123
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BMCBI
2006
174views more  BMCBI 2006»
15 years 15 days ago
CARAT: A novel method for allelic detection of DNA copy number changes using high density oligonucleotide arrays
Background: DNA copy number alterations are one of the main characteristics of the cancer cell karyotype and can contribute to the complex phenotype of these cells. These alterati...
Jing Huang, Wen Wei, Joyce Chen, Jane Zhang, Guoyi...
101
Voted
ISBI
2008
IEEE
16 years 1 months ago
Pathological image segmentation for neuroblastoma using the GPU
We present a novel use of GPUs (Graphics Processing Units) for the analysis of histopathologicalimages of neuroblastoma, a childhood cancer. Thanks to the advent of modern microsc...
Antonio Ruiz, Jun Kong, Manuel Ujaldon, Kim L. Boy...
98
Voted
MICCAI
2003
Springer
16 years 1 months ago
Assessing Early Brain Development in Neonates by Segmentation of High-Resolution 3T MRI
Abstract. This paper describes effort towards automatic tissue segmentation in neonatal MRI. Extremely low contrast to noise ratio (CNR), regional intensity changes due to RF coil ...
Guido Gerig, Marcel Prastawa, Weili Lin, John H. G...
110
Voted
TMI
2008
109views more  TMI 2008»
15 years 10 days ago
Efficient Multilevel Brain Tumor Segmentation With Integrated Bayesian Model Classification
Abstract-- We present a new method for automatic segmentation of heterogeneous image data that takes a step toward bridging the gap between bottom-up affinity-based segmentation me...
Jason J. Corso, Eitan Sharon, S. Dube, Suzie El-Sa...