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Example output of fiducial and label detection. The blue color component is shown, with boxed connected components in yellow. The fiducial locations are indicated as cyan and magenta asterisks. Letter labels, as output from the letter <t>recognition</t> function, are shown above the image patch in magenta. Here, all labels are correct except for “N”, which is mislabeled as “M”.
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Example output of fiducial and label detection. The blue color component is shown, with boxed connected components in yellow. The fiducial locations are indicated as cyan and magenta asterisks. Letter labels, as output from the letter recognition function, are shown above the image patch in magenta. Here, all labels are correct except for “N”, which is mislabeled as “M”.

Journal: Proceedings of SPIE--the International Society for Optical Engineering

Article Title: Textual fiducial detection in breast conserving surgery for a near-real time image guidance system

doi: 10.1117/12.2550662

Figure Lengend Snippet: Example output of fiducial and label detection. The blue color component is shown, with boxed connected components in yellow. The fiducial locations are indicated as cyan and magenta asterisks. Letter labels, as output from the letter recognition function, are shown above the image patch in magenta. Here, all labels are correct except for “N”, which is mislabeled as “M”.

Article Snippet: Letters can be recognized with 89% accuracy using the MATLAB built in optical character recognition function, and an average of 81% of points can be accurately labeled and localized.

Techniques:

Examples of blue color component image patches that were fed into the optical character recognition function and mislabeled. The output label is displayed in magenta. The fiducial location, as determined by the brightest pixel in the red color channel (not shown), is indicated with a cyan and magenta asterisk.

Journal: Proceedings of SPIE--the International Society for Optical Engineering

Article Title: Textual fiducial detection in breast conserving surgery for a near-real time image guidance system

doi: 10.1117/12.2550662

Figure Lengend Snippet: Examples of blue color component image patches that were fed into the optical character recognition function and mislabeled. The output label is displayed in magenta. The fiducial location, as determined by the brightest pixel in the red color channel (not shown), is indicated with a cyan and magenta asterisk.

Article Snippet: Letters can be recognized with 89% accuracy using the MATLAB built in optical character recognition function, and an average of 81% of points can be accurately labeled and localized.

Techniques: