An Improved DCT-Based JND Model Based on Textural Feature

Lecture Notes in Computer Science - Multi-disciplinary Trends in Artificial Intelligence ◽

10.1007/978-3-319-26181-2_20 ◽

2015 ◽

pp. 217-225 ◽

Cited By ~ 2

Author(s):

Bo Huang ◽

XiuZhi Yang ◽

KaiXiong Su ◽

MingKui Zheng

Keyword(s):

Textural Feature ◽

Model Based

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Statistical textural feature and deformable model based MR brain tumor segmentation

2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) ◽

10.1109/icacci.2016.7732121 ◽

2016 ◽

Cited By ~ 4

Author(s):

Shoaib Amin Banday ◽

Ajaz Hussain Mir

Keyword(s):

Brain Tumor ◽

Deformable Model ◽

Tumor Segmentation ◽

Textural Feature ◽

Brain Tumor Segmentation ◽

Model Based ◽

Mr Brain

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Statistical textural feature and deformable model based brain tumor segmentation and volume estimation

Multimedia Tools and Applications ◽

10.1007/s11042-016-3979-9 ◽

2016 ◽

Vol 76 (3) ◽

pp. 3809-3828 ◽

Cited By ~ 9

Author(s):

Shoaib Amin Banday ◽

Ajaz Hussain Mir

Keyword(s):

Brain Tumor ◽

Volume Estimation ◽

Deformable Model ◽

Tumor Segmentation ◽

Textural Feature ◽

Brain Tumor Segmentation ◽

Model Based

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

2020 ◽

Vol 43 ◽

Author(s):

Peter Dayan

Keyword(s):

Decision Theory ◽

Predictive Coding ◽

Bayesian Decision Theory ◽

Bayesian Decision ◽

Model Based ◽

Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

Microscopy and Microanalysis ◽

10.1017/s1431927600028968 ◽

2001 ◽

Vol 7 (S2) ◽

pp. 578-579

Author(s):

David W. Knowles ◽

Sophie A. Lelièvre ◽

Carlos Ortiz de Solόrzano ◽

Stephen J. Lockett ◽

Mina J. Bissell ◽

...

Keyword(s):

Image Analysis ◽

Mammary Epithelial Cells ◽

Nuclear Organization ◽

Critical Role ◽

Quantitative Model ◽

Mammary Epithelial ◽

Cell Phenotype ◽

Proliferating Cells ◽

Mitotic Apparatus ◽

Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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