2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDBIO-2.4
Paper Title UNITOPATHO, A LABELED HISTOPATHOLOGICAL DATASET FOR COLORECTAL POLYPS CLASSIFICATION AND ADENOMA DYSPLASIA GRADING
Authors Carlo Alberto Barbano, Daniele Perlo, Enzo Tartaglione, Attilio Fiandrotti, Luca Bertero, Paola Cassoni, Marco Grangetto, University of Turin, Italy
SessionBIO-2: Biomedical Signal Processing 2
LocationArea D
Session Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Poster
Topic Biomedical Signal Processing: Medical image analysis
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Abstract Histopathological characterization of colorectal polyps allows to tailor patients' management and follow up with the ultimate aim of avoiding or promptly detecting an invasive carcinoma. Colorectal polyps characterization relies on the histological analysis of tissue samples to determine the polyps malignancy and dysplasia grade. Deep neural networks achieve outstanding accuracy in medical patterns recognition, however they require large sets of annotated training images. We introduce UniToPatho, an annotated dataset of 9536 hematoxylin and eosin (H&E) stained patches extracted from 292 whole-slide images, meant for training deep neural networks for colorectal polyps classification and adenomas grading. We present our dataset and provide insights on how to tackle the problem of automatic colorectal polyps characterization by suggesting a multi-resolution deep learning approach.