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Facilitating Ultrastructural Pathology through Automated Imaging and Analysis
by
Dragomir, Anca
, Ryner, Martin
, Sladoje, Nataša
, Wetzer, Elisabeth
, Suveer, Amit
, Lindblad, Joakim
, Lidayová, Kristína
, Sintorn, Ida-Maria
, Hultenby, Kjell
in
Computerized Image Processing
/ Datoriserad bildbehandling
2019
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Facilitating Ultrastructural Pathology through Automated Imaging and Analysis
by
Dragomir, Anca
, Ryner, Martin
, Sladoje, Nataša
, Wetzer, Elisabeth
, Suveer, Amit
, Lindblad, Joakim
, Lidayová, Kristína
, Sintorn, Ida-Maria
, Hultenby, Kjell
in
Computerized Image Processing
/ Datoriserad bildbehandling
2019
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Do you wish to request the book?
Facilitating Ultrastructural Pathology through Automated Imaging and Analysis
by
Dragomir, Anca
, Ryner, Martin
, Sladoje, Nataša
, Wetzer, Elisabeth
, Suveer, Amit
, Lindblad, Joakim
, Lidayová, Kristína
, Sintorn, Ida-Maria
, Hultenby, Kjell
in
Computerized Image Processing
/ Datoriserad bildbehandling
2019
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Facilitating Ultrastructural Pathology through Automated Imaging and Analysis
Journal Article
Facilitating Ultrastructural Pathology through Automated Imaging and Analysis
2019
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Overview
Transmission electron microscopy (TEM) is an important diagnostic tool for analyzing human tissue at the nm scale. It is the only option, or gold standard, for diagnosing several disorders e.g. cilia and renal diseases, rare cancers etc. However, conventional TEM microscopes are highly manual, technically complex and a special environment is required to house the bulky and sensitive machines. Interpretation of information is subjective, time consuming, and relies on a high level of expertise which, unfortunately, is rare for this specialty within pathology. Here, we present methods and results from an ongoing project with the goal to develop a smart and easy to use platform for ultrastructural pathologic diagnoses. The platform is based on the recently developed MiniTEM instrument, a highly automated table-top TEM. In the project we develop image analysis methods for guided as well as fully automated search and analysis of structures of interest. In addition we enrich MiniTEM with an integrated database for convenient image handling and traceability. These points are identified by user representatives as crucial for creating a cost-effective diagnostic platform. We will show strategies and results for using image analysis and machine learning for automated search for objects/regions of interest at low magnification as well as combining multiple object instances acquired at high magnification to enhance nm details necessary for correct diagnosis. This will be exemplified for diagnosing primary cilia dyskinesia and renal disorders. The automation in imaging and analysis within the platform is a big step towards digital ultrapathology.
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