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2021 | OriginalPaper | Chapter

Delving into High Quality Endoscopic Diagnoses

Authors : Zhipeng Luo, Lixuan Che, Jianye He

Published in: Pattern Recognition. ICPR International Workshops and Challenges

Publisher: Springer International Publishing

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Abstract

This paper introduces the solution to the Detection Task and Segmentation Task of ICPR 2020 EndoTect Challenge [7] from the DeepBlueAI Team. The Detection Task is essentially a classification problem whose target is to distinguish between 23 types of digestive system diseases. For this task, we try different data augmentation methods and feature representation networks. Ensemble learning is also adopted to improve classification performance. For the Segmentation Task, we implement it in both semantic segmentation manner and instance segmentation manner. In comparison, semantic segmentation gets a relatively better result.

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previous chapter A Hierarchical Multi-task Approach to Gastrointestinal Image Analysis

next chapter Medical Diagnostic by Data Bagging for Various Instances of Neural Network

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Title: Delving into High Quality Endoscopic Diagnoses
Authors: Zhipeng Luo
Lixuan Che
Jianye He
Publisher: Springer International Publishing
Book: Pattern Recognition. ICPR International Workshops and Challenges
Print ISBN: 978-3-030-68792-2

Electronic ISBN: 978-3-030-68793-9

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-68793-9_20

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