TMARKER
TMARKER assists in cell nuclei counting and staining estimation of pathological immunohistochemical TMA images and non-TMA images.
Two main scenarios are adressed with TMARKER:
- You want to know how many cell nuclei on the image are positive and negative for a certain protein. Therefore, you already did an immunohistochemical staining experiment. TMARKER provides reproducable, stable and accurate cell counting and staining estimation assistance with color deconvolution.
- For staining estimation, you only want to consider one type of cells in the image (e.g. only relevant cancer cells). TMARKER provides modern machine learning algorithms that detect these relevant cells in the image and perform staining estimation only on these cells. Also this procedure is reproducable, stable and transferable.
Visit NEXUS.ethz.ch for more information and download.
Academic Partners:
- ETH Zurich, Switzerland,
- NEXUS Personalized Health Technologies, Switzerland
- University Spital Zurich, Switzerland
Can't render Publication.
BibTeXKey missing from Bibliography: schuffler_tmarker:_2013
BibTeXKey missing from Bibliography: schuffler_tmarker:_2013
TMARKER: A Robust and Free Software Toolkit for Histopathological Cell Counting and Immunohistochemical Staining Estimations.
Peter J. Schueffler, Niels Rupp, Cheng S. Ong, Joachim M. Buhmann, Thomas J. Fuchs and Peter J. Wild.
German Society of Pathology 97th Annual Meeting, 2013
PDF URL BibTeX Endnote / RIS Abstract
Download BibTeX citation
@inproceedings{schueffler_tmarker:_2013,
title = {{TMARKER}: {A} {Robust} and {Free} {Software} {Toolkit} for {Histopathological} {Cell} {Counting} and {Immunohistochemical} {Staining} {Estimations}},
url = {http://link.springer.com/article/10.1007%2Fs00292-013-1765-2},
abstract = {Aims. Assessment of immunhistochemical staining intensity and percentage of positive cells generally suffers from high inter- and intra-observer variability. Besides, estimation of the intensity and percentage of immunostained cells often involves manual cell counting and is therefore time consuming.
Methods. A novel, free, and open-source software toolkit was developed, connecting already available work flows for computational pathology and immunohistochemical tissue assessment with modern active learning algorithms from machine learning and computer vision.
Results. A new and platform independent software program, called TMARKER, was developed and introduced. The validity and robustness of the used algorithms has been shown on a test dataset of human renal clear cell carcinomas and prostate carcinomas.
Conclusions. This new software program together with a user-friendly Java-based graphical user interface enabled comprehensive computational assistance in pathological tissue rating. Routine use of this software toolkit may provide more reliable and robust biomarkers for treatment decision.},
booktitle = {German {Society} of {Pathology} 97th {Annual} {Meeting}},
author = {Schueffler, Peter J. and Rupp, Niels and Ong, Cheng S. and Buhmann, Joachim M. and Fuchs, Thomas J. and Wild, Peter J.},
year = {2013},
}
title = {{TMARKER}: {A} {Robust} and {Free} {Software} {Toolkit} for {Histopathological} {Cell} {Counting} and {Immunohistochemical} {Staining} {Estimations}},
url = {http://link.springer.com/article/10.1007%2Fs00292-013-1765-2},
abstract = {Aims. Assessment of immunhistochemical staining intensity and percentage of positive cells generally suffers from high inter- and intra-observer variability. Besides, estimation of the intensity and percentage of immunostained cells often involves manual cell counting and is therefore time consuming.
Methods. A novel, free, and open-source software toolkit was developed, connecting already available work flows for computational pathology and immunohistochemical tissue assessment with modern active learning algorithms from machine learning and computer vision.
Results. A new and platform independent software program, called TMARKER, was developed and introduced. The validity and robustness of the used algorithms has been shown on a test dataset of human renal clear cell carcinomas and prostate carcinomas.
Conclusions. This new software program together with a user-friendly Java-based graphical user interface enabled comprehensive computational assistance in pathological tissue rating. Routine use of this software toolkit may provide more reliable and robust biomarkers for treatment decision.},
booktitle = {German {Society} of {Pathology} 97th {Annual} {Meeting}},
author = {Schueffler, Peter J. and Rupp, Niels and Ong, Cheng S. and Buhmann, Joachim M. and Fuchs, Thomas J. and Wild, Peter J.},
year = {2013},
}
Download Endnote/RIS citation
TY - CONF
TI - TMARKER: A Robust and Free Software Toolkit for Histopathological Cell Counting and Immunohistochemical Staining Estimations
AU - Schueffler, Peter J.
AU - Rupp, Niels
AU - Ong, Cheng S.
AU - Buhmann, Joachim M.
AU - Fuchs, Thomas J.
AU - Wild, Peter J.
AB - Aims. Assessment of immunhistochemical staining intensity and percentage of positive cells generally suffers from high inter- and intra-observer variability. Besides, estimation of the intensity and percentage of immunostained cells often involves manual cell counting and is therefore time consuming.
Methods. A novel, free, and open-source software toolkit was developed, connecting already available work flows for computational pathology and immunohistochemical tissue assessment with modern active learning algorithms from machine learning and computer vision.
Results. A new and platform independent software program, called TMARKER, was developed and introduced. The validity and robustness of the used algorithms has been shown on a test dataset of human renal clear cell carcinomas and prostate carcinomas.
Conclusions. This new software program together with a user-friendly Java-based graphical user interface enabled comprehensive computational assistance in pathological tissue rating. Routine use of this software toolkit may provide more reliable and robust biomarkers for treatment decision.
C3 - German Society of Pathology 97th Annual Meeting
DA - 2013///
PY - 2013
UR - http://link.springer.com/article/10.1007%2Fs00292-013-1765-2
ER -
TI - TMARKER: A Robust and Free Software Toolkit for Histopathological Cell Counting and Immunohistochemical Staining Estimations
AU - Schueffler, Peter J.
AU - Rupp, Niels
AU - Ong, Cheng S.
AU - Buhmann, Joachim M.
AU - Fuchs, Thomas J.
AU - Wild, Peter J.
AB - Aims. Assessment of immunhistochemical staining intensity and percentage of positive cells generally suffers from high inter- and intra-observer variability. Besides, estimation of the intensity and percentage of immunostained cells often involves manual cell counting and is therefore time consuming.
Methods. A novel, free, and open-source software toolkit was developed, connecting already available work flows for computational pathology and immunohistochemical tissue assessment with modern active learning algorithms from machine learning and computer vision.
Results. A new and platform independent software program, called TMARKER, was developed and introduced. The validity and robustness of the used algorithms has been shown on a test dataset of human renal clear cell carcinomas and prostate carcinomas.
Conclusions. This new software program together with a user-friendly Java-based graphical user interface enabled comprehensive computational assistance in pathological tissue rating. Routine use of this software toolkit may provide more reliable and robust biomarkers for treatment decision.
C3 - German Society of Pathology 97th Annual Meeting
DA - 2013///
PY - 2013
UR - http://link.springer.com/article/10.1007%2Fs00292-013-1765-2
ER -
Aims. Assessment of immunhistochemical staining intensity and percentage of positive cells generally suffers from high inter- and intra-observer variability. Besides, estimation of the intensity and percentage of immunostained cells often involves manual cell counting and is therefore time consuming.
Methods. A novel, free, and open-source software toolkit was developed, connecting already available work flows for computational pathology and immunohistochemical tissue assessment with modern active learning algorithms from machine learning and computer vision.
Results. A new and platform independent software program, called TMARKER, was developed and introduced. The validity and robustness of the used algorithms has been shown on a test dataset of human renal clear cell carcinomas and prostate carcinomas.
Conclusions. This new software program together with a user-friendly Java-based graphical user interface enabled comprehensive computational assistance in pathological tissue rating. Routine use of this software toolkit may provide more reliable and robust biomarkers for treatment decision.
TMARKER: A User-Friendly Open-Source Assistance for Tma Grading and Cell Counting.
Peter J. Schueffler, Thomas J. Fuchs, Cheng S. Ong, Peter Wild and Joachim M. Buhmann.
Histopathology Image Analysis (HIMA) Workshop at the 15th International Conference on Medical Image Computing and Computer Assisted Intervention MICCAI, 2012
PDF URL BibTeX Endnote / RIS Abstract
Download BibTeX citation
@inproceedings{schueffler_tmarker:_2012,
title = {{TMARKER}: {A} {User}-{Friendly} {Open}-{Source} {Assistance} for {Tma} {Grading} and {Cell} {Counting}},
booktitle = {Histopathology {Image} {Analysis} ({HIMA}) {Workshop} at the 15th {International} {Conference} on {Medical} {Image} {Computing} and {Computer} {Assisted} {Intervention} {MICCAI}},
author = {Schueffler, Peter J. and Fuchs, Thomas J. and Ong, Cheng S. and Wild, Peter and Buhmann, Joachim M.},
year = {2012},
}
title = {{TMARKER}: {A} {User}-{Friendly} {Open}-{Source} {Assistance} for {Tma} {Grading} and {Cell} {Counting}},
booktitle = {Histopathology {Image} {Analysis} ({HIMA}) {Workshop} at the 15th {International} {Conference} on {Medical} {Image} {Computing} and {Computer} {Assisted} {Intervention} {MICCAI}},
author = {Schueffler, Peter J. and Fuchs, Thomas J. and Ong, Cheng S. and Wild, Peter and Buhmann, Joachim M.},
year = {2012},
}
Download Endnote/RIS citation
TY - CONF
TI - TMARKER: A User-Friendly Open-Source Assistance for Tma Grading and Cell Counting
AU - Schueffler, Peter J.
AU - Fuchs, Thomas J.
AU - Ong, Cheng S.
AU - Wild, Peter
AU - Buhmann, Joachim M.
C3 - Histopathology Image Analysis (HIMA) Workshop at the 15th International Conference on Medical Image Computing and Computer Assisted Intervention MICCAI
DA - 2012///
PY - 2012
ER -
TI - TMARKER: A User-Friendly Open-Source Assistance for Tma Grading and Cell Counting
AU - Schueffler, Peter J.
AU - Fuchs, Thomas J.
AU - Ong, Cheng S.
AU - Wild, Peter
AU - Buhmann, Joachim M.
C3 - Histopathology Image Analysis (HIMA) Workshop at the 15th International Conference on Medical Image Computing and Computer Assisted Intervention MICCAI
DA - 2012///
PY - 2012
ER -