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Related Concept Videos

Directionality of Nuclear Transport01:42

Directionality of Nuclear Transport

Ras-related nuclear protein or Ran is a small G protein that cycles between its GTP and GDP bound states. Ran specific regulators, a Ran GTPase Activating Protein or RanGAP present in the cytosol and a Ran guanine nucleotide exchange factor or RanGEF present inside the nucleus regulate GTP/GDP exchange. A high concentration of GTP inside the cells, in addition to this asymmetric distribution of  Ran-specific regulators, leads to a higher RanGTP concentration inside the nucleus. This...
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Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
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An optimal transportation approach for nuclear structure-based pathology.

Wei Wang1, John A Ozolek, Dejan Slepčev

  • 1Center for Bioimage Informatics, Biomedical Engineering Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA. wwang2@andrew.cmu.edu

IEEE Transactions on Medical Imaging
|October 28, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a new method using optimal transportation metrics to quantify nuclear structure from histopathology images. This approach accurately classifies tissue types, aiding in cancer diagnosis from liver and thyroid samples.

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Area of Science:

  • Computational pathology
  • Digital image analysis
  • Biomedical engineering

Background:

  • Nuclear morphology in histopathology images provides diagnostic clues for tissue lesions.
  • Quantitative analysis of nuclear structure is lacking for many diagnostic challenges.
  • Current methods struggle to quantify subtle differences in nuclear morphology from image data.

Purpose of the Study:

  • To develop and validate a method for characterizing and contrasting nuclear structure distribution in different tissue classes.
  • To enable precise quantitative information about nuclear morphology for improved diagnostics.
  • To apply the developed method to real-world surgical pathology diagnostic challenges.

Main Methods:

  • Quantifying chromatin morphology using the optimal transportation (Kantorovich-Wasserstein) metric.
  • Employing Fisher discriminant analysis and multidimensional scaling techniques.
  • Applying the method to histopathology images of liver and thyroid tissues for classification.

Main Results:

  • The optimal transportation metric effectively measures biological information, enabling automatic classification of nuclei (e.g., normal vs. cancer).
  • Classification accuracies achieved were comparable or superior to existing numerical features.
  • The technique revealed potentially biologically relevant differences in nuclear structure in liver and thyroid cancers.

Conclusions:

  • The developed method provides a robust quantitative approach to nuclear structure analysis in histopathology.
  • This quantitative method shows promise for improving diagnostic accuracy in surgical pathology.
  • The findings highlight the potential of computational methods in advancing cancer diagnostics.