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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

A systematic review on application of deep learning in digestive system image processing.

Huangming Zhuang¹, Jixiang Zhang¹, Fei Liao¹

¹Gastroenterology Department, Renmin Hospital of Wuhan University, Wuhan, 430060 Hubei China.

The Visual Computer

|November 8, 2021

Summary

Artificial intelligence (AI) in gastroenterology enhances disease diagnosis and treatment, particularly in areas like endoscopy and pathology. This technology shows significant potential for improving patient care and aiding physicians in the near future.

Keywords:

Artificial intelligence Deep learning Diagnosis Digestive system Endoscopic Imaging Pathology

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Area of Science:

Medical Artificial Intelligence
Gastroenterology
Digestive System Diseases

Background:

The big data era has spurred the application of artificial intelligence (AI), especially deep learning, in medicine.
AI has achieved significant success in gastroenterology, including endoscopy, imageology, and pathology.
AI applications span various digestive diseases such as benign lesions, early cancer, tumors, inflammatory bowel diseases, and liver/pancreas conditions.

Purpose of the Study:

To summarize recent advancements in AI for diagnosing and treating digestive system diseases.
To discuss the future potential and applications of AI in gastroenterology.

Main Methods:

Review of current research on artificial intelligence in gastroenterology.
Analysis of AI applications in diagnostic accuracy and physician workload reduction.
Exploration of AI's role in computer-aided diagnosis and image processing.

Main Results:

Computer-aided diagnosis using AI significantly improves diagnostic accuracy.
AI tools help reduce the workload of physicians, providing clinical decision support.
Deep learning has demonstrated remarkable accomplishments across various gastroenterological subfields.

Conclusions:

Artificial intelligence holds high value and significant potential for the future of medicine, particularly in gastroenterology.
AI facilitates the application and development of computer-aided image processing in gastroenterology.
This work aims to support gastroenterologists and computer experts in AI research within digestive diseases.