A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development

Autor: Marcin Grzegorzek, Jinghua Zhang, Tao Jiang, Chen Li, Xiaoyan Li, Changhao Sun, Mamunur Rahaman, Shiliang Ai, Yu-Dong Yao, Hong Li
Rok vydání: 2020
Předmět:
medicine.medical_specialty
Diagnostic information
Feature extraction
Color
02 engineering and technology
Review Article
General Biochemistry
Genetics and Molecular Biology
Machine Learning
03 medical and health sciences
0302 clinical medicine
Imaging
Three-Dimensional
Stomach Neoplasms
Image Interpretation
Computer-Assisted
0202 electrical engineering
electronic engineering
information engineering
Image Processing
Computer-Assisted
Medicine
Humans
Diagnosis
Computer-Assisted
Poisson Distribution
Histological examination
General Immunology and Microbiology
business.industry
digestive
oral
and skin physiology
Stomach
Cancer
Reproducibility of Results
General Medicine
State of the art review
Gold standard (test)
medicine.disease
digestive system diseases
Computer-Aided Design
020201 artificial intelligence & image processing
Histopathology
Radiology
business
030217 neurology & neurosurgery
Algorithms
Zdroj: BioMed Research International
BioMed Research International, Vol 2021 (2021)
ISSN: 2314-6141
Popis: Gastric cancer is a common and deadly cancer in the world. The gold standard for the detection of gastric cancer is the histological examination by pathologists, where Gastric Histopathological Image Analysis (GHIA) contributes significant diagnostic information. The histopathological images of gastric cancer contain sufficient characterization information, which plays a crucial role in the diagnosis and treatment of gastric cancer. In order to improve the accuracy and objectivity of GHIA, Computer-Aided Diagnosis (CAD) has been widely used in histological image analysis of gastric cancer. In this review, the CAD technique on pathological images of gastric cancer is summarized. Firstly, the paper summarizes the image preprocessing methods, then introduces the methods of feature extraction, and then generalizes the existing segmentation and classification techniques. Finally, these techniques are systematically introduced and analyzed for the convenience of future researchers.
Databáze: OpenAIRE
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