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Genome Annotation and Assembly

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Annotation Tools in Gastrointestinal Polyp Annotation.

Ola Selnes¹, Thomas Bjørsum-Meyer^1,2, Aymeric Histace³

¹Department of Surgery, Odense University Hospital, 5700 Svendborg, Denmark.

Diagnostics (Basel, Switzerland)

|October 27, 2022

Summary

This summary is machine-generated.

Capsule endoscopy annotation tools are vital for training deep neural networks. This review details current systems for gastrointestinal polyp annotation, highlighting needs for better user overviews and feature specificity.

Keywords:

annotation tool automated labelling camera capsule endoscopy computer-aided diagnosis polyp annotation

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Area of Science:

Gastroenterology
Medical Imaging
Artificial Intelligence

Background:

Capsule endoscopy (CE) offers an alternative to traditional gastrointestinal (GI) endoscopy.
Accurate annotation of CE images is essential for creating datasets to train deep neural networks (DNNs).
Existing annotation systems for GI polyp pathology require further evaluation.

Purpose of the Study:

To provide a comprehensive overview of current annotation systems used in capsule endoscopy.
To focus on the specific challenges and requirements for annotating adenomatous polyps in the GI tract.
To identify gaps in current knowledge regarding user needs and essential features for polyp annotation.

Main Methods:

Literature review of described and in-use annotation systems for capsule endoscopy.
Analysis of systems focusing on gastrointestinal polyp annotation.
Evaluation of automated labeling features and their impact on time efficiency.

Main Results:

Various annotation systems for CE are available, with a focus on GI polyp pathology.
Some systems show promise in improving time efficiency through automated labeling.
There is a lack of comprehensive data on user-specific needs and necessary features for effective polyp annotation.

Conclusions:

Annotation tools are critical for advancing DNN-based analysis in capsule endoscopy.
Further research is needed to optimize annotation systems for GI polyp detection.
Standardized overviews and feature-specific analyses are required to guide the development of superior annotation tools.