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Related Concept Videos

Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
276
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

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Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
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Compartment Models: Single-Compartment Model01:14

Compartment Models: Single-Compartment Model

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The single-compartment model serves as a simplified representation of the human body. This model assumes that the body functions as a single, well-mixed open compartment. When a drug is administered intravenously, it enters the body and quickly distributes uniformly. The drug then undergoes biotransformation and elimination, ultimately leaving the body. The volume of this compartment is referred to as the apparent volume of distribution into which the drug can uniformly distribute. In this...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
249
Molecular Models02:00

Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

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Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
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Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving SSLE of Glass Crystals
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Data-Driven Indoor Scene Modeling from a Single Color Image with Iterative Object Segmentation and Model Retrieval.

Mingming Liu, Kexin Zhang, Jie Zhu

    IEEE Transactions on Visualization and Computer Graphics
    |November 13, 2018
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    Summary

    This study introduces a novel method for indoor scene modeling from single images. The system uses user-defined bounding boxes to retrieve and align 3D models, improving scene reconstruction accuracy.

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    Area of Science:

    • Computer Vision
    • Computer Graphics
    • Artificial Intelligence

    Background:

    • Accurate indoor scene modeling from single images remains a challenge.
    • Existing methods struggle with cluttered backgrounds and occlusions.

    Purpose of the Study:

    • To develop an automated method for indoor scene modeling from a single color image.
    • To improve the accuracy and robustness of 3D model retrieval and scene reconstruction.

    Main Methods:

    • User interaction via semantic bounding boxes to identify objects of interest.
    • Iterative object segmentation and 3D model retrieval from the ShapeNet repository.
    • A unified multi-labeling framework for simultaneous object segmentation.
    • A novel scene layout estimation method using segmentation masks.

    Main Results:

    • Successfully models indoor scenes from single color images.
    • Demonstrates improved accuracy and robustness against clutter and occlusions.
    • Achieves remarkable improvements in scene composition through layout estimation.

    Conclusions:

    • The proposed method effectively models indoor scenes by integrating object segmentation and 3D model retrieval.
    • The iterative approach and unified framework enhance segmentation and retrieval accuracy.
    • Scene layout estimation significantly boosts the overall scene modeling performance.