Preview

Sechenov Medical Journal

Advanced search

Automated analysis of intestinal polyps images

Abstract

Using image analysis software calculates the distribution of points of polyp bowel picture brightness and color, as well as the rate of brightness and color gradients. Next, using statistical analysis founds connection with clinical indicators of image characteristics. It was found that the calculated characteristics allow to determine accurately the diagnosis. 

About the Authors

I. V. Yarema
Moscow Medical and Dental University named after A.I. Yevdokimov
Russian Federation

MD, corresp. member of RAS, honored scientist of Russia, dean of the medical faculty



A. N. Gerasimov
I.M. Sechenov First MSMU
Russian Federation

Andrej Nikolaevich Gerasimov, Doctor of physical and mathematical sciences, associate prof., head of the chair of medical informatics and statistics

8-2 Trubetskaya str., Moscow, 119991

tel.: 8 (905) 550-50-84



N. F. Lebedeva
City Clinical Hospital № 5 of the Department of Health of Moscow
Russian Federation

PhD, head of the Endoscopy Department

 



O. M. Kharkova
City Clinical Hospital № 5 of the Department of Health of Moscow
Russian Federation

endoscopist of Endoscopy department



A. A. Atayan
I.M. Sechenov First MSMU
Russian Federation

PhD, assistant of the chair of hospital surgery № 2



References

1. Киселев А.С. Краткая история формирования ряда областей медицинской науки и видов высокотехнологичной помощи для взрослых пациентов (обзор) // Сеченовский вестник. 2014; 16(4): 2-14. [Kiselev A.S. A brief history of the formation of a number of medical science branches and kinds of high-tech medical care for adult patients (review) // Sechenovsky vestnik. 2014; 16(4): 2-14.]

2. Атлас эндоскопии пищеварительного тракта: возможности высокого разрешения и изображения в узком световом спектре / Под ред. Дж. Коэна; пер. с англ.; под ред. А.А. Будзинского. М. «Логосфера». 2012. 360 с. [Atlas of endoscopy of the digestive tract: the possibility of high-resolution images in the narrow light spectrum / Ed. by J. Cohen, A.A. Budzinsky; transl. from English. M. «Logosfera». 2012. 360 p.]

3. Kanao H., Tanaka S., Oka S. et al. Narrow-band imaging magnifi cation predicts the histology and invasion depth of colorectal tumors // Gastrointest. Endosc. 2009. 69 (3 Suppl.): 631–636.

4. Konishi K. et al. A comparison of magnifying and nonmagnifying colonoscopy for diagnosis of colorectal polyps: A prospective study // Gastrointest. Endosc. 2003 Jan; 57(1): 48-53.

5. Mashida H., Sano Y., Hamamoto Y., Muto M., Kozu T., Tajiri H., Yoshida S. NBI for diff erential diagnosis of colorectal mucosal lesions: a pylot study // Endoscopy. 2004; 36: 1094-1098.

6. Sano Y., Horimatsu T., Fu Ki et al. Magnifi ed observation of microvascular architecture of colorectal lesions using NBI for the diff erential diagnosis between non-neoplastic and neoplastic colorectal lesion: a prospective study // Gastrointest. Endoscop. 2006; 63: AB102.

7. Endoscopic prediction of deep submucosal invasive carcinoma: validation of the Narrow-Band Imaging International Colorectal Endoscopic (NICE) classifi cation. Department of Endoscopy, Hiroshima University Hospital, Hiroshima, Japan 2013 Jul 30. pii: S0016-5107(13)01853-1. doi: 10.1016 j.gie.2013.04.185.

8. Герасимов А.Н. Медицинская статистика. М. МИА. 2007. 480 с. [Gerasimov A.N. Medical statistics. M. MIA. 2007. 480 p.]


Review

Views: 58


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2218-7332 (Print)
ISSN 2658-3348 (Online)