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EndoAbS Dataset

Veronica Penza


MARC21 XML Export

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    <subfield code="a">&lt;p&gt;The &lt;strong&gt;EndoAbS Dataset&lt;/strong&gt; (Endoscopic Abdominal Stereo Images Dataset) aims to provide to the computer assisted surgery community a dataset for the validation of 3D reconstruction algorithms.&lt;br&gt;
It is composed of:&lt;br&gt;
- 120 pair of endoscopic stereo images of abdominal organs (liver, kidneys, spleen);&lt;br&gt;
- corresponding ground truth in left-camera reference frame, generated using a laser scanner;&lt;br&gt;
- camera calibration parameters;&lt;/p&gt;

&lt;p&gt;The images were captured under different conditions:&lt;br&gt;
- different light levels;&lt;br&gt;
- presence of smoke; &amp;nbsp;&lt;br&gt;
- two phantom-endoscope distances (~5cm or ~10cm);&lt;br&gt;
&amp;nbsp;&lt;br&gt;
If you use this dataset, please cite:&lt;br&gt;
&amp;nbsp;&lt;br&gt;
&amp;nbsp;Penza, V., Ciullo, A. S., Moccia, S., Mattos, L. S., &amp;amp; De Momi, E. (2018). EndoAbS dataset: Endoscopic abdominal stereo image dataset for benchmarking 3D stereo reconstruction algorithms. &lt;em&gt;The International Journal of Medical Robotics and Computer Assisted Surgery&lt;/em&gt;, e1926.&lt;/p&gt;

&lt;p&gt;For further information, please contact veronica.penza@iit.it&lt;/p&gt;</subfield>
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    <subfield code="x">Penza, V., Ortiz, J., Mattos, L. S., Forgione, A., &amp; De Momi, E. (2016).</subfield>
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    <subfield code="x">and surgery, 11(2), 197-206.</subfield>
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