Computer-Aided Diagnosis System for Detection of Stomach Cancer with Image Processing Techniques.
Computerized decision support(CDS) system
Image processing
Region growing
Segmentation
Statistical region merging
Statistical region merging with region growing
Stomach cancer
Journal
Journal of medical systems
ISSN: 1573-689X
Titre abrégé: J Med Syst
Pays: United States
ID NLM: 7806056
Informations de publication
Date de publication:
14 Mar 2019
14 Mar 2019
Historique:
received:
27
12
2018
accepted:
11
02
2019
entrez:
16
3
2019
pubmed:
16
3
2019
medline:
6
8
2019
Statut:
epublish
Résumé
Stomach cancer is a type of cancer that is hard to detect at an early stage because it gives almost no symptoms at the beginning. Stomach cancer is an increasing incidence of cancer both in the World as well as in Turkey. The most common method used worldwide for gastric cancer diagnosis is endoscopy. However, definitive diagnosis is made with endoscopic biopsy results. Diagnosis with endoscopy is a very specific and sensitive method. With high-resolution endoscopy it is possible to detect mild discolorations, bulges and structural changes of the surface of the mucosa. However, because the procedures are performed with the eye of a doctor, it is possible that the cancerous areas may be missed and / or incompletely detected. Because of the fact that the cancerous area cannot be completely detected may cause the problem of cancer recurrence after a certain period of surgical intervention. In order to overcome this problem, a computerized decision support system (CDS) has been implemented with the help of specialist physicians and image processing techniques. The performed CDS system works as an assistant to doctors of gastroenterology, helping to identify the cancerous area in the endoscopic images of the scaffold, to take biopsies from these areas and to make a better diagnosis. We believe that gastric cancer will be helpful in determining the area and biopsy samples taken from the patient will be useful in determining the area. It is therefore considered a useful model.
Identifiants
pubmed: 30874907
doi: 10.1007/s10916-019-1203-y
pii: 10.1007/s10916-019-1203-y
doi:
Types de publication
Journal Article
Langues
eng
Pagination
99Subventions
Organisme : Selçuk Üniversitesi
ID : 15101020
Références
Tree Physiol. 2000 Oct;20(16):1113-20
pubmed: 11269963
Methods Mol Biol. 2009;472:467-77
pubmed: 19107449
J Med Syst. 2016 Jan;40(1):31
pubmed: 26553064
Magn Reson Imaging. 2016 Nov;34(9):1292-1304
pubmed: 27477599
Diagn Histopathol. 1981 Oct-Dec;4(4):307-33
pubmed: 6802623
Am J Cardiol. 1997 Sep 15;80(6):736-40
pubmed: 9315579