Journal: Diagnostic Pathology

Article Title: Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome

doi: 10.1186/s13000-018-0739-3

Figure Lengend Snippet: Sketch of the analysis. A) ROI tumor (not shown) and the ROI border (dashed red line) were manually delineated by a pathologist (CW). A1: a sliding window moved over the ROI border and cropped every half TMA diameter in the underlying, TMA core-sized image. A2: The resulting tile (exactly the size of one TMA core) was then defined as a virtual TMA (vTMA). b , c This procedure leads to a value (number of tumor buds or budding score) per vTMA. This spatial data could be plotted as a heat map (example heat maps with arbitrary values in the left part) or as a histogram (right part of the figure)

Article Snippet: Subsequently, all grid points within the above specified ROI were loaded on the basis of the Omero-MATLAB-toolbox and saved as a TMA core object (containing the slide ID, the core name and position, and an IHC image of the core).

Techniques:

Journal: Diagnostic Pathology

Article Title: Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome

doi: 10.1186/s13000-018-0739-3

Figure Lengend Snippet: Definition and detection of tumor buds. a Example single TMA core stained for pan-cytokeratin and hematoxylin and eosin (HE). The red circle highlights a tumor bud next to larger tumor island. The blue circle is a small tumor part, which we referred to as a “tumor islet”; which is a small tumor aggregate but does not meet all criteria for a tumor bud. b Histogram of pan-cytokeratin positive tumor area per core (upper plot) and pan-cytokeratin tumor bud area per core (lower plot). One can see that the mean area of all tumor fragments (upper panel) shows a huge dispersion (x-axis 0–100,000), whereas the mean area of the tumor buds is less distributed (x-axis 0–1000)

Article Snippet: Subsequently, all grid points within the above specified ROI were loaded on the basis of the Omero-MATLAB-toolbox and saved as a TMA core object (containing the slide ID, the core name and position, and an IHC image of the core).

Techniques: Staining, Dispersion

Journal: Methods (San Diego, Calif.)

Article Title: Metadata management for high content screening in OMERO

doi: 10.1016/j.ymeth.2015.10.006

Figure Lengend Snippet: Metadata storage and retrieval in OMERO. The drawing shows the different types of metadata supported within OMERO and how they are stored. All these metadata are accessible in OMERO clients through the API presented by the OMERO server.

Article Snippet: For analysis functions using Matlab, a fully developed Matlab API is available for reading from and writing to OMERO (see for example ).

Techniques: