Capsule Endoscopy


Automatic Detection of Gastrointestinal Tract Lesions

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Overview:

GastroIntestinal Track diagnoser (GITdiagnoser) aims at the development of a Computer-aided Diagnosis (CAD) system for aid in the diagnosis of gastrointestinal track (GIT) lesions in clinical based on videos of wireless capsule endoscopy (VCE). The main output is CAD prototype to be evaluated in the Gastroenterology service of the Centro Hospitalar Universitário do Porto (CHUP), Porto.

Main Task Goals:

Private Dataset Creation

To create a wide private and anonymized dataset of wireless endoscopic videos with medical annotations.

Informative Regions Identification

Classify the pixels of the VCE images as informative or non-informative to create a map of the informational regions of the image.

Anatomical Location

Classify the VCE images according to the part of the GI tract (esophagus, stomach, small intestine, and large intestine), and estimates the displacement between images.

Abnormalities Detection

Detect candidates for abnormalities, i.e., different occurrences from that which appears in tests considered normal to include pathologies of the GI tract and classifies them as abnormalities or non-abnormalities.

Abnormalities Classification

Classification of the detected abnormalities in the various types of known lesions/pathologies or as an unknown abnormality.

Visualization Interface

Producing a user-friendly interface that will allow the reviewer to navigate through the VCE, to view detected anomalies and to annotate the VCE that can later added to the database.

Publications

Articles in Conference Proceedings
Teresa Valério, Sara Gomes, Marta Salgado, Hélder Oliveira and António Cunha, Lesions Multiclass Classification in Endoscopic Capsule Frames, International Conference on Health and Social Care Information Systems and Technologies (HCist), Sousse, Tunisa, 16-18 October, 2019 (Accepted).
Sara Gomes,Teresa Valério, Marta Salgado, Hélder Oliveira and António Cunha, Unsupervised Neural Network for Homography Estimation in Capsule Endoscopy Frames, International Conference on Health and Social Care Information Systems and Technologies (HCist), Sousse, Tunisa, 16-18 October, 2019 (Accepted).
Gil Pinheiro, Paulo Coelho, Mariana Mourão, Marta Salgado, Hélder P. Oliveira, António Cunha, Small bowel mucosa segmentation for frame characterization in videos of endoscopic capsules, IEEE International Symposium on Biomedical Imaging (ISBI), Venice, Italy, 8-11 April 2019. DOI: 10.1109/ISBI.2019.8759598. IEEE
Articles in Conference Proceedings
Gil Pinheiro, Paulo Coelho, Marta Salgado, Hélder P. Oliveira, António Cunha, Deep Homography Based Localization on Videos of Endoscopic Capsules, IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIMB), Madrid, Spain, 3-6 December 2019, pp. 724-727. DOI: 10.1109/BIBM.2018.8621450. IEEE
Paulo Coelho, Ana Pereira, Argentina Leite, Marta Salgado, António Cunha, A Deep Learning Approach for Red Lesions Detection in Video Capsule Endoscopies, International Conference on Image Analysis and Recognition (ICIAR), Porto, Portugal, 27-29 June 2019. DOI: 10.1007/978-3-319-93000-8_63. Springer